No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
A-Pool: An agent-oriented open system shell for distributed decision process modeling
Abstract
An agent‐oriented open system shell, A‐Pool, for distributed decision process modeling in the Internet domain is presented. Unlike most decision support systems, A‐Pool provides a testbed for modeling and understanding the cognitive aspects of distributed decision processes themselves rather than for domain‐specific problem solving. This is achieved with a pool of virtual agents and a pool of cognitive maps of the agents at each A‐Pool node. The virtual agent scheme extends object‐oriented programming to the Internet domain and supports different communication and collaboration protocols with virtual communities, virtual sessions, and virtual conferences. The cognitive map scheme supports perspective sharing and various conflict integration and resolution strategies through cognitive map composition, derivation, and focus generation. Thus each A‐Pool node provides an architecture for modeling interdependencies and for ensuring global coherence; in addition, the communication is asynchronous and the control is distributed, allowing a large degree of autonomy and the examination of various thoughts and social protocols involved in strategic planning in an open system environment. Basic ideas are illustrated with a running example.
... We now introduce the Contraction Mapping Theorem [62]. ...
... for all x, y ∈ X, then ϕ is said to be a contraction of X into X. Theorem 1. [62] If X is a complete metric space, and if ϕ is a contraction of X into X, then there exists one and only one x ∈ X such that ϕ(x) = x. ...
... In other words, ϕ has a unique fixed point. The uniqueness follows from the fact that if ϕ(x) = x and ϕ(y) = y, then (3) gives d(x, y) ≤ cd(x, y), which can only happen when d(x, y) = 0 (See [62]). Equation (2) can be written as: ...
... This chapter is based on ideas presented in (Zhang 2003a,b;2005a,b;2009a,b,c,d). Early works of this line of research can be found in (Zhang, Chen & Bezdek 1989) ) (Zhang, Wang & King 1994) ...
... This chapter is based on the ideas presented in (Zhang 1996(Zhang , 1998(Zhang , 2005a(Zhang ,b, 2006a(Zhang ,b, 2007(Zhang , 2009b. Early works of this line of research can be found in (Zhang, Chen & Bezdek 1989) ) (Zhang, Wang & King 1994) ...
... This chapter is based on the ideas presented in (Zhang 2003a(Zhang ,b, 2005a(Zhang ,b, 2006a. Early works of this line of research can be found in (Zhang, Chen & Bezdek 1989) ) (Zhang, Wang & King 1994) ...
YinYang bipolar relativity can trace its philosophical origins to ancient Chinese YinYang cosmology, which claims that everything has two sides or two opposite, but reciprocal, poles or energies. More specifically, this discipline is intended to be a logical unification of general relativity and quantum mechanics. YinYang Bipolar Relativity: A Unifying Theory of Nature, Agents and Causality with Applications in Quantum Computing, Cognitive Informatics and Life Sciences presents real-world applications of YinYang bipolar relativity that focus on quantum computing and agent interaction. This unique work makes complex theoretical topics, such as the ubiquitous effects of quantum entanglement, logically comprehendible to a vast audience.
(This file includes a Table of Content followed by a Preface.)
(Preface: https://www.igi-global.com/pdf.aspx?tid=109360&ptid=45961&ctid=15&t=Preface&isxn=9781609605254)
... While indigenous research is looking for its logical foundation, a formal YinYang logic has already arrived in the literature. The logic was evolved from its earlier version named BNPN logic^(negative-positive-neutral logic) and was originally used for cognitive mapping, organizational modeling, and decision analysis (Zhang, 1996(Zhang, , 2003aZhang, Chen, & Bezdek, 1989;Zhang, Chen, Wang, & King, 1992;Zhang, Wang, & King, 1994). Bipolar fuzzy set theory was first introduced in 1994 (Zhang, 1994) and later extended to a YinYang bipolar fuzzy set theory (Zhang, 1998), which was recognized (cf. ...
... & The cognitive-map-based model is focused on bipolar cognitive mapping for BDOM/EBDA. It is applicable in holistic decision analysis, especially in strategic decision analysis (Zhang, 2011;Zhang et al., 1992Zhang et al., , 1994. & The quantum model derives its organizational modeling power from quantum biocellular structures (Zhang, 2011(Zhang, , 2012a(Zhang, , b, 2013. ...
While it is recognized that indigenous research on China is helpful if not essential, the essence of YinYang has never been made clear in logical forms. While indigenous research should be guided by a philosophy, it was widely believed that without a unique logical system China only had culture but no philosophy. Now, worldwide indigenous research on China is faced with tremendous difficulties due to the lack of principles, academic disciplines, and a scientific common ground even though the Chinese YinYang has been widely influential. Consequently, a unique formal logical foundation is imperative for a logical reincarnation of Chinese philosophy. It is shown in this work that a formal equilibrium-based and harmony-centered YinYang bipolar dynamic logic (BDL) can fill the gap. Based on BDL, bipolar dynamic organizational modeling (BDOM) is proposed for equilibrium-based decision analysis (EBDA). It is shown that BDOM/EBDA methodologies can integrate case study methods and grounded theory together into a holistic and dynamic management paradigm for global regulation. The three philosophies of metaphysics, dialectics and the Dao of YinYang are formally classified and distinguished. It is argued that with BDL YinYang is elevated to a formal logical system, and indigenous research on China is positioned in the context of a global science with a common philosophical ground of equilibrium, complementarity, and harmony. It is concluded that, with YinYang as a philosophical guiding light, not only is bipolar dynamic equilibrium-based indigenous research helpful but also fundamental and essential.
... Axelrod (1976) used a cognitive map to represent tacit knowledge in the political and social sciences. The cognitive map has also been successfully applied in such areas as decision making in a complex war game (Klein and Cooper 1982), strategic planning (Ramaprasad and Poon 1985), information retrieval (Johnson and Briggs 1994), and distributed decision process modeling (Zhang et al. 1994). A cognitive map is composed of nodes, signed directed arcs, and causality values. ...
... A time variable was introduced into cognitive maps (Park and Kim 1995) so that they could be applied to cases varying with time. Recently, cognitive map has also been used for distributed decision process modeling on networks (Zhang et al. 1994), decision analysis (Zhang et al., 1989), stock investment analysis problems (Lee and Kim 1997), and business process redesign (Kwahk and Kim 1999). ...
With the advent of the Internet, the electronic B2B negotiation process has drawn increasing attention from both researchers
and practitioners. However, the literature still shows that only structured negotiation terms (SNTs) are being explicitly
considered, despite the fact that unstructured negotiation terms (UNTs) should be rendered as well. This chapter proposes
a new negotiation support mechanism that can be utilized to incorporate causal relationships between SNTs and UNTs in the
process of B2B negotiation, by using a cognitive map. The proposed negotiation mechanism suggests that cognitive maps could
be used to represent causal relationships between SNTs and UNTs, both as knowledge representation vehicles and as inference
engines. After reviewing the potential of cognitive map in B2B negotiation, we implemented a prototype, CAKES-NEGO, which
we then used in illustrative examples in order to examine the validity of our proposed mechanism. The mechanism was tested
using two practical scenarios: a structured, twenty-one item questionnaire was developed and applied in order to evaluate
the mechanism’s validity based on the responses of eleven graduate students. In addition, statistical tests proved that the
proposed negotiation mechanism could improve decision performance significantly in B2B negotiations.
... Without systematically investigating and analyzing that causality existent among those design factors, decision makers are not able to perform appropriate steps of simulation to adjust the EC sites. In this sense, we introduce a technique of cognitive map (Lee & Kim, 1997;Zhang, Wang, & King, 1994) to incorporate causality into adjusting the EC sites more satisfactorily. Therefore, we propose research objectives as follows: ...
... Lee, Courtney, and O'Keefe (1992) developed collective cognitive modeling (COCOMAP) to support group cognitive processes and organizational learning through cognitive modeling. Recently, cognitive map has been used for a distributed decision process modeling on the Internet domain (Zhang et al., 1994), a stock investment analysis problem (Lee & Kim, 1997), and business process redesign (Kwahk & Kim, 1999). ...
The electronic commerce (EC) has been widely studied in the academic as well as practical fields. Especially, a lot of special topics regarding the EC such as B2C and B2B have been investigated in literature. However, there are much less studies about the EC sites themselves. Besides, only a few studies exist about the issues regarding how to adjust the design factors of the EC sites. The main objective of this study is to fill this research void by employing two techniques: (1) cognitive map and (2) linear structural relationship (LISREL). The cognitive map was used to operationalize the causal relationships among design factors of the EC sites, and investigate the simulation to find the optimal strategy of adjusting the design factors. The LISREL was performed to prove the proposed research model, where original Technology Acceptance Model (TAM) [Davis MIS Q. 13 (1989) 319] is adopted as a basic framework for providing causal relationships. Usable questionnaires were collected from 114 respondents who are proved to be qualified for this study. They were educated to surf two typical EC sites appropriately and tested before answering the questionnaires. Those respondents who completed questionnaires successfully were given a book coupon of 5$ equivalent. After LISREL experiments, the proposed research model was tested, and an adjacency matrix was induced which is to be used for the cognitive map simulation. With the adjacency matrix and 15 hypothetical market situations, the cognitive map simulations were successfully performed yielding that the proposed two techniques could be used for successfully adjusting the design factors of the EC sites under consideration in line with the changes in customers' tastes and market situations. One of the noticeable practical advantages of this study is that decision makers can identify the most relevant design factors and thereby allocate limited resources to them reasonably by performing the cognitive map simulation in advance before doing design adjustment to the EC sites in actuality.
... If both disciplines can be integrated, a holistic view of the area can be obtained, allowing developments in both areas to proceed in a balanced manner. Much research in the area of group supporting technologies has mostly been experimentally based (Gray, 1987;Lewis, 1987;Dennis et al., 1990;Smith and Vanecek, 1990;Dickson et al., 1993;Zhang et al., 1994;Davenport and Travica, 1995), making it dif® cult to replicate the natural process of the decision making group. The organizational setting is a richer location for studies into the advancement of group supporting technologies, as it would provide a comprehensive picture of group decision making in a real environment (Kraemer and King, 1988). ...
A major problem facing the development of technological support for groups is that many studies investigate group technology in isolation from an analysis of group activity, or focus only on discrete aspects of the process. This paper presents the findings of a study that investigated the nature and extent of group decision making and the use of group supporting technology in Irish organizations. The paper presents a model of group decision making and examines group processes and activities as well as the use of technology at each stage. The findings indicate that group decision making is a widespread phenomenon, which was found to be far more complicated than individual decision making. However, groups were found to need a great deal of control and coordination to enable members to collaborate effectively. Nevertheless, group decision making was found to receive little technological support. The available technology provided only low level support which mainly focused on supporting the asynchronous work of groups.
... Bonham, Shapiro & Trumble 1979), decision and coordination (e.g. Zhang et al., 1989;1992;Zhang, Wang & King 1994;Zhang 1996;Zhang, 2003aZhang, , 2003bZhang, , 2006a, operational research (e.g. Klein & Cooper 1982;Montibeller et. ...
This chapter presents a review on the quest for logically definable causality. The limitation of observability and truth-based cognition is discussed. The student-teacher philosophical dispute between Aristotle and Plato is revisited. Aristotle’s causality principle, David Hume’s challenge, Lotfi Zadeh’s “Causality Is Undefinable” conclusion, and Judea Pearl’s probabilistic definability are reviewed. Niels Bohr’s particle-wave complementarity principle, David Bohm’s causal interpretation of quantum mechanics, and Sorkin’s causal set program are discussed. Cognitive-map-based causal reasoning is briefly visited. YinYang bipolar logic and bipolar causality are previewed. Social construction and destruction in science are examined. It is asserted that, in order to continue its role as the doctrine of science, the logical definability of Aristotle’s causality principle has become an ultimate dilemma of science. It is concluded that, in order to resolve the dilemma, a formal system with logically definable causality has to be developed, which has to be logical, physical, relativistic, and quantum in nature. The formal system has to be applicable in the microscopic world as well as in the macroscopic world, in the physical world as well as in the social world, in cognitive informatics as well as in life sciences, and, above all, it has to reveal the ubiquitous effects of quantum entanglement in simple, comprehensible terms.
... FCMs describe expert knowledge of complex systems with high dimensions and a variety of factors. An increased interest about the theory and application of FCMs in complex systems has been also noted, and their validity and usefulness has been proved in the various fields (Eden & Ackermann, 1989;Eden, Jones, & Sims, 1979;Kwahk & Kim, 1999;Lee & Kwon, 2006;Lee & Kwon, 2008;Nelson, Nadkarni, Narayanan, & Ghods, 2000;Zhang, Chen, & Bezdek, 1989;Zhang, Wang, & King, 1994). On the other hand, the usefulness of FCMs inspires many researchers and practitioners in various fields to construct their own FCM, and it is common that they have created myriads of similar cognitive maps again and again despite of the existence of similar FCMs. ...
... Several authors have developed and applied the CM technique with the aim of imitating human reasoning and thinking. Furthermore, the studies upon the CM technique are highly adopted in different application fields such as network system (Zhang et al., 1994), decisions analysis (Axelrod, 1976), and business process redesign (Kwahk and Kim, 1999) in order to solve distributed decision making process. In addition, inference engine for causal and diagnostic reasoning was introduced by Kim and Pearl (1987) according to Pearl's causal network formalism. ...
... Research in Axelrod (1976) and Perusich (1996) have used FCM for representing tacit knowledge in political and social analysis. FCMs have been successfully applied to various fields such as decision making in complex war games (Klein & Cooper, 1982), strategic planning (Diffenbach, 1982;Ramaprasad & Poon, 1985), information retrieval (Johnson & Briggs, 1994) and distributed decision process modeling (Zhang, Wang, & King, 1994). Research like (Lee & Kim, 1997) has successfully applied FCMs to infer rich implications from stock market analysis results. ...
... Research in Axelrod (1976) and Perusich (1996) have used FCM for representing tacit knowledge in political and social analysis. FCMs have been successfully applied to various fields such as decision making in complex war games (Klein & Cooper, 1982), strategic planning (Diffenbach, 1982;Ramaprasad & Poon, 1985), information retrieval (Johnson & Briggs, 1994) and distributed decision process modeling (Zhang, Wang, & King, 1994). Research like Lee and Kim (1997) has successfully applied FCMs to infer rich implications from stock market analysis results. ...
This paper presents the application of a fuzzy cognitive map (FCM) based theoretical framework and its associated modeling and simulation tool to strategy maps (SMs). Existing limitations of SMs are presented in a literature survey. The need for scenario based SMs with inherited ability to change scenarios dynamically as well as the missing element of time are highlighted and discussed upon. FCMs are presented as an alternative to overcome these shortfalls with the introduction of fuzziness in their weights and the robust calculation mechanism. An FCM tool is presented that allows simulation of SMs as well as interconnection of nodes (performance measures) in different SMs which enables the creation of SM hierarchies. An augmented FCM calculation mechanism that allows this type of interlinking is also presented. The resulting methodology and tool are applied to two Banks and the results of these case studies are presented.
... Research in Axelrod (1976) and Perusich (1996) have used FCM for representing tacit knowledge in political and social analysis. FCMs have been successfully applied to various fields such as decision making in complex war games (Klein and Cooper, 1982), strategic planning (Diffenbach, 1982;Ramaprasad and Poon, 1985), information retrieval (Johnson and Briggs, 1994) and distributed decision process modelling (Zhang et al., 1994). Research like that of Lee and Kim (1997) has successfully applied FCMs to infer rich implications from stock market analysis results. ...
This paper addresses the problem of designing a knowledge management methodology tool to act as a decision support mechanism for geographically dispersed financial enterprises. The underlying research addresses the problem of information capture and representation in financial institutions in order to provide an implementation of the virtuous cycle of knowledge flow. The proposed methodology tool utilizes the fuzzy causal characteristics of Fuzzy Cognitive Maps (FCMs) to generate a hierarchical and dynamic network of interconnected financial performance concepts. By using FCMs, the proposed mechanism simulates the operational efficiency of distributed organizational models with imprecise relationships and quantifies the impact of the geographically dispersed activities to the overall business model. Generic adaptive maps that supplement the decision-making process present a roadmap for integrating hierarchical FCMs into the business model of typical financial sector enterprises. Copyright © 2004 John Wiley & Sons, Ltd.
... Research in [2] and [49] have used FCM for representing tacit knowledge in political and social analysis. FCMs have been successfully applied to various fields such as decision making in complex war games [27], strategic planning [11], [50], information retrieval [21] and distributed decision process modeling [62]. Research like [34] has successfully applied FCMs to infer rich implications from stock market analysis results. ...
This paper addresses the problem of designing an “intelligent” decision support methodology tool to act as a back end to financial
planning. The methodology tool proposes a novel approach to supplementing typical financial strategy formulation projects
by utilizing the fuzzy causal characteristics of Fuzzy Cognitive Maps (FCMs) to generate a hierarchical and dynamic network
of interconnected profit and loss (P&L) concepts. By using FCMs, the mechanism simulates the efficiency of complex hierarchical
financial models with imprecise relationships and external stimuli while quantifying the impact of strategic changes to the
overall P&L status. Generic maps that supplement the decision making process demonstrate a roadmap for integrating hierarchical
FCMs into the P&L model of typical financial sector enterprises. Preliminary experiments indicate that ex ante reasoning of the impact of strategic changes (actual or hypothetical) to the status of financial performance can be effective
and realistic, without employing detailed P&L numerical calculations.
KeywordsFuzzy cognitive maps-financial performance management-strategy planning-banking-profit and loss accounts
... (Axelrod 1976) and (Perusich 1996) have used FCM for representing tacit knowledge in political and social analysis. FCMs have been successfully applied to various fields such as decision making in complex war games (Klein and Cooper 1982), strategic planning (Diffenbach 1982;Ramaprasad and Poon 1985), strategic information systems planning (Kardaras and Karakostas 1999), information retrieval (Johnson and Briggs 1994) and distributed decision modelling (Zhang, Wang et al. 1994). ...
This paper describes a model for software reliability prediction. The output is a ‘forward-looking’ model, which helps testers
to predict and manage software reliability. Despite the availability of various approaches developed in the field of software
reliability, there are still issues that require further research in order to succeed in supporting the decision making process
and improving software quality. In the present paper we propose the use of Fuzzy Cognitive Maps (FCMs) as an approach to modelling
of software reliability. FCMs capture information in the relationships between concepts, are dynamic, express hidden relationships,
and are combinable and tunable. Preliminary experiments indicate that the proposed mechanism forms a sound support aid for
software reliability modelling.
KeywordsSoftware Reliability-Fuzzy Cognitive Maps-Modelling-Uncertainty
... Research [2] and [43] have used FCM for representing tacit knowledge in political and social analysis. FCMs have been successfully applied to various fields such as decision making in complex war games [25], strategic planning [11,44], information retrieval [20] and distributed decision process modeling [53]. Research like [30] has successfully applied FCMs to infer rich implications from stock market analysis results. ...
Fund management is a major function for most financial sector enterprises with geographically dispersed activities. The risk associated to such managerial decisions affects directly the continuity, profitability and reputation of the enterprise. This paper presents a knowledge modeling methodology tool to act as a decision support mechanism for geographically dispersed financial enterprises. The underlying research addresses the problem of financial information capture and representation by utilizing the soft computing characteristics of Fuzzy Cognitive Maps (FCMs). By using FCMs, the proposed mechanism generates a hierarchical and dynamic network of interconnected financial knowledge concepts, simulates the operational efficiency of distributed organizational models with imprecise relationships and quantifies the impact of geographically dispersed activities to the overall business performance. Generic adaptive maps offer an alternative approach to financial management based on strategic level knowledge modeling and integrate hierarchical FCMs into the decision making model of typical financial sector enterprises. Finally, this paper discusses experiments with the proposed mechanism and comments on its usability.
... Lee et al. (1992) developed COCOMAP (Collective Cognitive Modeling) to support group cognitive processes and organizational learning through cognitive modeling. Recently, cognitive map has been used for decision analysis (Zhang et al., 1989), a distributed decision process model in the Internet domain (Zhang, Wang, & King, 1994), wayfinding process (Chen & Stanney, 1999), a stock investment analysis problem (Lee & Kim, 1997), business process redesign (Kwahk & Kim, 1999), knowledge management (Noh, Lee, Kim, Lee, & Kim, 2000), bosphorus crossing problem (Ulengin, Topcu, & Sahin, 2001) diagnosis of language impairment (Georgopoulos, Malandraki, & Stylios, 2002), and design of agents (Miao, Goh, Miao, & Yang, 2002), the design of electronic commerce web sites (Lee & Lee, 2003). ...
This paper proposes the usage of fuzzy cognitive map (FCM) for the evaluation of electronic data interchange (EDI) performance. Although there has been a stream of research on the performance of EDI systems during the last decades, possible interrelationships among those individual factors of EDI performance have been largely ignored and thereby were not adequately examined.The main task of evaluation of EDI performance demands consideration of the complex causal relationship among EDI performance factors. It is difficult even for experts in organizational behavior to cognitively predict the causal effect of one factor on the others. A FCM is used to describe the inference process for the evaluation of EDI performance. Initially, structural equation models are used for identifying relevant relationships among the factors and indicating their direction and strength. This study collected data from the 202 companies, which already experienced EDI systems implementation. The derived five factors include reduction of processing time, improved information quality, decreased processing cost, improved operational efficiency, competitive advantage. Findings indicate that a causal model of EDI performance adequately capture each of the proposed variables. The cognitive map provides preliminary insights into the causal model of EDI performance.
... Cognitive maps have been found especially useful in solving problems where many decision variables and uncontrollable variables are causally interrelated with each other. Recently, cognitive map has been used for decision analysis (Zhang, Chen, & Bezdek, 1989), a distributed decision process model in the Internet domain (Zhang, Wang, & King, 1994), wayfinding process (Chen & Stanney, 1999), a stock investment analysis problem (Lee & Kim, 1997), business process redesign (Kwahk & Kim, 1999), knowledge management (Noh, Lee, Kim, Lee, & Kim, 2000), bosphorus crossing problem (Ulengin, Topcu, & Sahin, 2001), diagnosis of language impairment (Georgopoulos, Malandraki, & Stylios, 2003), design of agents (Miao, Goh, Miao, & Yang, 2002), and design of electronic commerce web sites (Lee & Lee, 2003). ...
It is difficult even for experts in organizational behavior to cognitively predict the causal effect of one factor on the others. A cognitive map is used to describe the inference process for the investigation of online community voluntary behavior. The investigation of online community voluntary behavior demands consideration of the complex causal effect from support for member communication, perceived community value, recognition for contribution, freedom of expression, and interactive communication, to community commitment, loyalty, and social participation. A standardized causal coefficient estimated in structural equation models (SEMs) is used to create a cognitive map illustrating the effect of the status of one component on the status of another component. The cognitive map provides preliminary insights into the direction of online community voluntary behavior toward maximizing community commitment, loyalty, and social participation.
... Research by Axelrod (1976) and Perusich (1996) have used FCM for representing tacit knowledge in political and social analysis. FCMs have been successfully applied to various fields such as decisionmaking in complex war games (Klein & Cooper, 1982), strategic planning (Diffenbach, 1982;Ramaprasad & Poon, 1985), information retrieval (Johnson & Briggs, 1994) and distributed decision process modeling (Zhang, Wang, & King, 1994). Research by Lee and Kim (1997) has successfully applied FCMs to infer rich implications from stock market analysis results. ...
This paper is concerned with proposing a fuzzy cognitive map (FCM) driven approach for implementing expert decision support in the area of urban design. Previous research activities modeled a knowledge-based system using first order predicate calculus. The current approach utilizes the inherent analogies between SLD resolution trees and FCMs and proposes the generation of multi-branch map hierarchies in order to model the disjointed conjuncts of the logic-based rules. This research proposes specific algorithms for interpreting the logic-based rules to FCMs as well as specific algorithms and formulas for calculating the values of multi-branch map hierarchies. Finally, this paper presents preliminary experiments and comments on the usefulness of the proposed methodology tool.
... Research in Axelrod (1976) and Perusich, 1996 have used FCM for representing tacit knowledge in political and social analysis. FCMs have been successfully applied to various fields such as decision making in complex war games (Klein & Cooper, 1982), strategic planning (Diffenbach, 1982;Ramaprasad & Poon, 1985), information retrieval (Johnson & Briggs, 1994) and distributed decision process modeling (Zhang, Wang, & King, 1994). Research like (Lee & Kim, 1997) has successfully applied FCMs to infer rich implications from stock market analysis results. ...
E-business has a significant impact on managers and academics. Despite the rhetoric surrounding e-business strategy formulation mechanisms, which support reasoning of the effect of strategic change activities to the maturity of the e-business models, are still emerging. This paper describes an attempt to build and operate such a reasoning mechanism as a novel supplement to e-business strategy formulation exercises. This new approach proposes the utilization of the fuzzy causal characteristics of Fuzzy Cognitive Maps (FCMs) as the underlying methodology in order to generate a hierarchical and dynamic network of interconnected maturity indicators. By using FCMs, this research aims at simulating complex strategic models with imprecise relationships while quantifying the impact of strategic changes to the overall e-business efficiency. This research establishes generic adaptive domains – maps in order to implement the integration of hierarchical FCMs into e-business strategy formulation activities. Finally, this paper discusses experiments with the proposed mechanism and comments on its usability.
... Lee, Courtney, and O'Keefe (1992) developed Collective Cognitive Modeling (COCOMAP) to support group cognitive processes and organizational learning through cognitive modeling. Recently, cognitive map has been used for a distributed decision process model in the Internet domain (Zhang, Wang, & King, 1994), a stock investment analysis problem (Lee & Kim, 1997), business process redesign (Kwahk & Kim, 1999), diagnosis of language impairment (Georgopoulos, Malandraki, & Stylios, 2002), and design of agents (Miao, Goh, Miao, & Yang, 2002). ...
This paper proposes the usage of fuzzy cognitive map (FCM) for the management of relationships among organizational members in airline service. The main task of relationship management demands consideration of the complex causal relationship among conflict, communication, balanced power, shared values, trust, and cooperation. It is difficult even for experts in organizational behavior to cognitively predict the causal effect of one factor on the others. FCM is used to describe the inference process for the relationship management in airline service. Initially, structural equation models are used for identifying relevant relationships among the factors and indicating their direction and strength. A standardized causal coefficient is then used to create a cognitive map illustrating the effect of the status of one component on the status of another component. The cognitive map provides preliminary insights into the direction of relationship management toward maximizing effectiveness of airline service.
This chapter presents the theory of bipolar relativity–a central theme of this book. The concepts of YinYang bipolar agents, bipolar adaptivity, bipolar causality, bipolar strings, bipolar geometry, and bipolar relativity are logically defined. The unifying property of bipolar relativity is examined. Space and time emergence from YinYang bipolar geometry is proposed. Bipolar relativity provides a number of predictions. Some of them are domain dependent and some are domain independent. In particular, it is conjectured that spacetime relativity, singularity, gravitation, electromagnetism, quantum mechanics, bioinformatics, neurodynamics, and socioeconomics are different phenomena of YinYang bipolar relativity; microscopic and macroscopic agent interactions in physics, socioeconomics, and life science are directly or indirectly caused by bipolar causality and regulated by bipolar relativity; all physical, social, mental, and biological action-reaction forces are fundamentally different forms of bipolar quantum entanglement in large or small scales; gravity is not necessarily limited by the speed of light; graviton does not necessarily exist.
abstractThe focus of this chapter is on cognitive mapping and cognitive-map-based (CM-based) decision analysis. This chapter builds a bridge from mental quantum gravity to social quantum gravity. It is shown that bipolar relativity, as an equilibrium-based unification of nature, agent and causality, is naturally the unification of quantum bioeconomics, brain dynamics, and socioeconomics as well. Simulated examples are used to illustrate the unification with cognitive mapping and CM-based multiagent decision, coordination, and global regulation in international relations.
As a continuation of Chapter 8, this chapter presents a theory of bipolar quantum bioeconomics (BQBE) with a focus on computer simulation and visualization of equilibrium, non-equilibrium, and oscillatory properties of YinYang-N-Element cellular network models for growing and degenerating biological processes. From a modern bioinformatics perspective, it provides a scientific basis for simulation and regulation in genomics, bioeconomics, metabolism, computational biology, aging, artificial intelligence, and biomedical engineering. It is also expected to serve as a mathematical basis for biosystem inspired socioeconomics, market analysis, business decision support, multiagent coordination and global regulation. From a holistic natural medicine perspective, diagnostic decision support in TCM is illustrated with the YinYang-5-Element bipolar cellular network; the potential of YinYang-N-Element BQCA in qigong, Chinese meridian system, and innate immunology is briefly discussed.
The learning and control space of real-world autonomous agents are often many-dimensional, growing, and unbounded in nature. Such agents exhibit adaptive, incremental, exploratory, and sometimes explosive learning behaviors, Learning in adaptive neurofuzzy control, however, is often referred to as global training with a large set of random examples and a very low learning rate. This type of controller is not reorganizable; it cannot explain exploratory learning behaviors as exhibited by human and animal species. A theory of coordinated computational intelligence (CCI) is proposed in this paper which leads to a reorganizable: multiagent cerebellar architecture for intelligent control, The architecture is based on the hypotheses that 1) a cerebellar system consists of a school of relatively simple and cognitively identifiable semiautonomous neurofuzzy agents; 2) autonomous control is the result of cerebellar agent fine-tuning and coordination rather than complicate computation; and 3) learning is accomplished via individual cerebellar agent learning and coordinated discovery in a leaning-tuning-brainstorming process. Agent-oriented decomposition and coordination algorithms are introduced; necessary and sufficient conditions are established for cerebellar agent discovery and common Sense cerebellar motion law discovery. Nesting, safety, layering, and autonomy-four principles are analytically formulated for the reorganization of neurofuzzy agents, The four Principles extend Saridis' principle of "increasing intelligence with decreasing precision" for hierarchical control to multiagent neurofuzzy control, and bridge a gap between neurofuzzy control and PID control, adaptive learning and exploratory learning, numerical learning and symbolic learning. Basic ideas are illustrated in legged locomotion and gymnastics. It is shown that, with agent-oriented decomposition, a single near-miss example can enable the cerebellar agents of a 3-link or 4-link uniped simulation to learn gymnastic jumps; a small number of fine-tuned agents can form a kernel community which can discover common sense cerebellar motion laws; and a kernel governed by the laws can grow with a geometrical learning rate. Implications of this work to human and animal locomotion control are discussed. Potential applications and extensions of the findings are outlined.
This paper presents the application of a Fuzzy Cognitive Map (FCM) based theoretical framework and its associated modeling and simulation tool to StrategyMaps (SMs). Existing limitations of SMs are presented in a literature survey. The need for scenario based SMs with inherited ability to change scenarios dynamically as well as the missing element of time are highlighted and discussed upon. FCMs are presented as an alternative to overcome these shortfalls with the introduction of fuzziness in their weights and the robust calculation mechanism. An FCM tool is presented that allows simulation of SMs as well as interconnection of nodes (performance measures) in different SMs which enable the creation of SM hierarchies. An augmented FCM calculation mechanism that allows this type of interlinking is also presented. The resulting methodology and tool are applied to two Banks and the results of these case studies are presented.
A survey on agents, causality and intelligence is presented and an equilibrium-based computing paradigm of quantum agents and quantum intelligence (QAQI) is proposed. In the survey, Aristotle’s causality principle and its historical extensions by David Hume, Bertrand Russell, Lotfi Zadeh, Donald Rubin, Judea Pearl, Niels Bohr, Albert Einstein, David Bohm, and the causal set initiative are reviewed; bipolar dynamic logic (BDL) is introduced as a causal logic for bipolar inductive and deductive reasoning; bipolar quantum linear algebra (BQLA) is introduced as a causal algebra for quantum agent interaction and formation. Despite the widely held view that causality is undefinable with regularity, it is shown that equilibrium-based bipolar causality is logically definable
using BDL and BQLA for causal inference in physical, social, biological, mental, and philosophical terms. This finding leads to the paradigm of QAQI where agents are modeled as quantum ensembles; intelligence is revealed as quantum intelligence. It is shown that the ensembles formation, mutation and interaction of agents can be described as direct or indirect results of quantum causality. Some fundamental laws of causation are presented for quantum agent entanglement and quantum intelligence. Applicability is illustrated; major challenges are identified in equilibrium based causal inference and quantum data mining.
A survey on agents, causality and intelligence is presented and an equilibrium-based computing
paradigm of quantum agents and quantum intelligence (QAQI) is proposed. In the survey, Aristotle’s
causality principle and its historical extensions by David Hume, Bertrand Russell, Lotfi Zadeh,
Donald Rubin, Judea Pearl, Niels Bohr, Albert Einstein, David Bohm, and the causal set initiative
are reviewed; bipolar dynamic logic (BDL) is introduced as a causal logic for bipolar inductive
and deductive reasoning; bipolar quantum linear algebra (BQLA) is introduced as a causal algebra
for quantum agent interaction and formation. Despite the widely held view that causality is undefinable
with regularity, it is shown that equilibrium-based bipolar causality is logically definable
using BDL and BQLA for causal inference in physical, social, biological, mental, and philosophical
terms. This finding leads to the paradigm of QAQI where agents are modeled as quantum ensembles;
intelligence is revealed as quantum intelligence. It is shown that the ensemble formation,
mutation and interaction of agents can be described as direct or indirect results of quantum causality.
Some fundamental laws of causation are presented for quantum agent entanglement and
quantum intelligence. Applicability is illustrated; major challenges are identified in equilibrium
based causal inference and quantum data mining.
Equilibrium-based computing is introduced and distinguished from truth-based computing. It is shown that object-oriented languages can be used for both equilibrium-based and truth-based programming. This observation supports the claim that any physical being must exist in certain dynamic equilibrium. The applicability of this approach is discussed and illustrated with Java and C++ code. It is shown that the equilibrium-based computing paradigm is applicable in both digital and quantum computing for particle-wave unification of matter and antimatter atoms.
Cognitive map is a well-known approach to model the dynamics of qualitative systems, and has been studied and used in various fields, such as psychology, education, engineering, and management. Although the validity and usefulness of cognitive maps has been proven in many fields, and a considerable number of cognitive maps have been built during the last decade, cognitive map construction and use was just one-off event. In addition, the high degree of cognitive complexities in large cognitive maps makes it difficult for others to understand and exploit the pre-defined cognitive map in another similar domain problem.
In this paper, an ontological semantic inference method, which combines the cognitive map and semantic influence, is proposed. This approach reuses a pre-defined cognitive map and provides an ontological semantic inference mechanism in decision making environments by reducing the degree of cognitive complexities in a large cognitive map.
Unstructured group decision-making is burdened with several central difficulties: unifying the knowledge of multiple experts in an unbiased manner and computational inefficiencies. In addition, a proper means of storing such unified knowledge for later use has not yet been established. Storage difficulties stem from of the integration of the logic underlying multiple experts' decision-making processes and the structured quantification of the impact of each opinion on the final product. To address these difficulties, this paper proposes a novel approach called the multiple agent-based knowledge integration mechanism (MAKIM), in which a fuzzy cognitive map (FCM) is used as a knowledge representation and storage vehicle. In this approach, we use particle swarm optimization (PSO) to adjust causal relationships and causality coefficients from the perspective of global optimization. Once an optimized FCM is constructed an agent based model (ABM) is applied to the inference of the FCM to solve real world problem. The final aggregate knowledge is stored in FCM form and is used to produce proper inference results for other target problems. To test the validity of our approach, we applied MAKIM to a real-world group decision-making problem, an IT project risk assessment, and found MAKIM to be statistically robust.
About 25 years ago, the Nobel laureate Herbert A. Simon and other top Management Science/Operations Research (MS/OR) and Artificial Intelligence (AI) researchers, suggested that an integration of the two disciplines would improve the design of decision-making support
tools in organizations. The suggested integrated system has been called an intelligent decision-making support system (i-DMSS).
In this chapter, we use an existing conceptual framework posed to assess the capabilities and limitations of the i-DMSS concept,
and through a conceptual metaanalysis research of the Decision Support System (DSS) and AI literature from 1980 to 2004, we develop a strategic assessment of the initial proposal. Such an analysis reveals
support gaps that suggest further development of the initial i-DMSS concept is needed. We offer recommendations for making
the indicated improvements in i-DMSS design, development, and application.
In this chapter, the potential of using Semantic Web technologies as part of an intelligent decision support system (DSS)
is discussed. The Semantic Web is introduced and its benefits to DSSs are highlighted. In addition, two Semantic Web ontologies
for DSSs are developed using the Protégé tool. The two ontologies are used to demonstrate their ability to infer new knowledge,
help visualize and improve data presentation, query data and allow global database linkage as a part of the Semantic Web;
this allows the ontologies to be processed by intelligent, Web-based software agents.
This paper presents a hybrid algorithm based on fuzzy linear regression (FLR) and fuzzy cognitive map (FCM) to deal with the problem of forecasting and optimization of housing market fluctuations. Due to the uncertainty and severe noise associated with the housing market, the application of crisp data for forecasting and optimization purposes is insufficient. Hence, in order to enable the decision-makers to make decisions with respect to imprecise/fuzzy data, FLR is used in the proposed hybrid algorithm. The best-fitted FLR model is then selected with respect to two indicators including Index of Confidence (IC) and Mean Absolute Percentage Error (MAPE). To achieve this objective, analysis of variance (ANOVA) for a randomized complete block design (RCBD) is employed. The primary objective of this study is to utilize imprecise/fuzzy data in order to improve the analysis of housing price fluctuations, in accordance with the factors obtained through the best-fitted FLR model. The secondary objective of this study is the exhibition of the resulted values in a schematic way via FCM. Hybridization of FLR and FCM provides a decision support system (DSS) for utilization of historical data to predict housing market fluctuation in the future and identify the influence of the other parameters. The proposed hybrid FLR-FCM algorithm enables the decision-makers to utilize imprecise and ambiguous data and represent the resulted values of the model more clearly. This is the first study that utilizes a hybrid intelligent approach for housing price and market forecasting and optimization.
The field of regional planning is characterized by the large number of issues and attributes involved, and regional planning
for aquaculture development is no exception. Moreover, aquacultural plans do not have clearly defined objectives and require
information that, if it exists, is often imprecise and uncertain. This chapter presents the development of an intelligent
decision support system (IDSS) for regional aquaculture planning. The IDSS applies fuzzy set theory to multiple criteria decision-making
(MCDM) in regional aquaculture planning. A case study from Egypt demonstrates the proposed IDSS and the fuzzy MCDM framework.
Faced with the imminent retirement of two senior employees who used to make decisions on bus allocations to customers manually,
a bus rental company in Seoul, South Korea, asked us to develop a DMSS (decision-making support system) to help the young
fresh graduate employee who will be taking over this job from them. Practice has shown that allocation and routing decisions
made manually by human operators with long experience are usually nearly optimal, and it is very hard to beat those decisions
using a computerized DMSS. Therefore the company asked us to design an i-DMSS (intelligent DMSS) that can help the new decision
maker to reach decisions comparable in quality to those made by the retiring pair of senior decision makers. In this paper
we discuss this decision problem, its context, the models we used to solve it, the algorithms we used in the i-DMSS to solve
these models, and how this i-DMSS is used to make the decisions daily. The i-DMSS is based on bipartite matching and transportation
algorithms and heuristics, and produces solutions 10–20% more economical than the manual decisions.
This chapter describes a new software product called the Planners Lab©. The software is a DSS—in this case an abbreviation
for Decision Support Simulator instead of the traditional Decision Support Systems. The software is intended to be used as a laboratory for academic teaching, research and consulting. Consequently, there
is no purchase cost for academic institutions to have access to the software on their computers. The chapter describes the
current state of the software, giving inferences to how this software can improve decision making. Several potential research
streams are described as well. The chapter ends with a discussion about the new breed of DSS developer.
This chapter reports the findings of exploratory research into the technical and organizational challenges facing i-DMSS for
nonoperational decision making and indicates directions for future research. Some challenges arise as a direct result of expert
judgments used to compensate for the lack of information inherent in complex, uncertain situations, and the necessity to support
intelligently the interaction between decision makers and experts, each of them having different backgrounds, interests, knowledge
and cognitive style. Another important challenge results from the manipulation and interpretation of information, especially
for expert judgments’ aggregation and the providing of advanced functionalities such as forecasting in the context of highly
uncertain and complex decisions.
This chapter traces the impact of decision support methods, including those based on Artificial Intelligence concepts, from
the beginning, through to the present, and concludes with proposals for the future of the profession. Most of the readers
of this book are engaged in the creation of models, systems, data and knowledge bases and methodologies. These are all worthwhile
tasks, and some of them are seriously complicated and tricky to do. Our goal in this chapter is to encourage colleagues to
move up a gear. Since the start in 1965, members of our profession have solved several thousand problems for organizations.
The next job is to tackle more worldclass issues. We have the skills and the tools to do this. The executives we work with
are more computer aware than they were in the 1960s. We ourselves know more about the need for social acceptance than before.
The chapter pencils in the history of the DSS concept from the start, then reviews the problems we are collectively tackling
now, before moving on to consider the global scale of the challenges that lie ahead.
This chapter addresses the complexities of inference-based decision making and the challenge of supporting such processes.
People are often unaware of the cognitive framework that facilitates and biases complex decisions. Inference-based decision
making is described as bidirectional reasoning. We show how the decision maker gradually makes sense of and simplifies the
decision task, how decision criteria can be modeled, and how criteria change as the decision-maker’s experience increases.
It is claimed that the prime way to aid inference-based decision making is to make the process of generating sense explicit,
and that experiments constitute an important tool.
Although traditional decision-making support systems (DMSS) have been researched extensively, few, if any, studies have addressed a unifying architecture for the evaluation of intelligent DMSS (i-DMSS). Traditional systems have often been evaluated in the literature on the basis of single-outcome measures, such as decreased cost, increased profit, or improved forecasting, compared to decision making without a DMSS. In cases in which other metrics are used for evaluation, process measures are most often cited, such as increased efficiency, organizational learning, and increased speed. Previous research by the authors has shown that a multicriteria evaluation for DMSS can be provided, combining both outcome and process measures into a single metric using the analytic hierarchy process (AHP). However, the specific categories that should be utilized as evaluation measures have not been defined, and no studies have focused exclusively on categories for the evaluation of i-DMSS. This chapter explores the concept of intelligence in general, and artificial intelligence in particular, as it relates to aiding decision making. It then proposes an architecture for the evaluation of i-DMSS and applies the model to empirical systems. The results are: (1) recognition of the contribution of AI to i-DMSS; (2) identification of the criterion (or criteria) used to evaluate i-DMSS; (3) categorization of the evaluation measures; (4) an architecture for evaluation for i-DMSS; and (5) recommendation of a multicriteria model to assess i-DMSS.
The recent massive use of wireless technology in the business domain strongly modified organization and management of work
and made it critical both to gather decision-problem data and to share them among human business agents in real-time. To support
this new generation of decision makers and face real-time in-the-field decision problems, we developed MicroDEMON, a language-based
user-centered mobile software system that represents a step further along the evolution of active DMSSs, a kind of intelligent
and proactive decision-making support systems.
A large amount of research on the development of decision-making support systems (DMSS) focuses on organizational issues,
technical issues, or both kinds of issues at the same time. Whereas it is widely recognized that these two categories represent
the dominant sources of issues that DSS builders had to overcome in the past, a third category, knowledge-management issues,
gradually surfaces. Bolstered by advances in information technology in general, and artificial intelligence in particular,
the field of knowledge management increases the number of development issues previously dealt with partly from an organizational
perspective and partly from a technical perspective, but rarely as a perspective of its own. This chapter reviews nine DMSS
development processes and methodologies according to their focus on organizational issues, technical issues, or both. It then
proposes an innovative framework for the design and development of DMSS with particular attention on knowledge management
issues and their relation with organizational and technical issues. It finally revisits two existing development processes
according to this framework.
In this chapter we review the knowledge-based view on decision support and argue the emergence of a new type of intelligent
decision support system — an intelligent gateway for supporting specific knowledge needs. The modern view on decision support
and expert systems has shifted from considering these as purely analytical tools for assessing best-decision options to seeing
them as a more comprehensive environment for supporting efficient information processing based on a good understanding of
the problem context. Such intelligent decision support systems incorporate problem-domain knowledge to improve their information
processing and provision capabilities. More recently, information portals have been proposed as tools for matching users’
information needs in order to enhance their decision-making ability. This chapter looks at portals as new types of intelligent
decision support systems, which use problem-domain knowledge in order to improve efficiency in information provision. The
main focus of the chapter is on suggesting mechanisms for implementing intelligent decision support capabilities in a healthcare
portal, which seeks to deliver personalized information to support efficient decision making. BCKOnline, a healthcare portal
built around breast cancer information, is described as an example of such implementation.
With the advent of the Internet era and the maturation of electronic commerce, strategic avatar design has become an important way of keeping up with market changes and customer tastes. In this study, we propose a new DSS for an adaptive avatar design that uses a cognitive map (CM) as a what-if simulation vehicle. The main virtue of the proposed avatar design recommendation DSS (abbreviated as ADR-DSS) is its ability to change specific avatar design features with objective consideration of the subsequent effects upon other design features, thereby enhancing user satisfaction. An avatar represents a user's self-identity and desire for self-disclosure. Therefore, the claim is made that there is a relationship between the characteristics of avatar design features and the choice of avatar. The considerations in this study are props (garments, facial expression, and miscellaneous) and subjective judgments (self-image and user satisfaction). The results of both brainstorming and focus group interviews with a group of avatar experts were used to objectively organize the CM. All the experts who participated are currently working in developing and designing avatar features in portal websites. Incorporating the CM as a model base, the proposed ADR-DSS was implemented, and two scenarios were presented for illustration. To prove the validity of the ADR-DSS, a rigorous survey was performed, obtaining statistically significant results.
The use of the Internet in the daily activities of individuals and firms has become entrenched, and online shopping has become commonplace. However, debates about how online shopping recommendation mechanisms (OREMs) should be designed have not been completely resolved. The challenge with traditional online shopping recommendation mechanisms (TR-OREMs) is that they focus too much on quantitative factors. Thus, they ignore causal interrelationships with qualitative factors that are believed to significantly impact quantitative factors. Considering only quantitative factors and ignoring qualitative ones likely distorts the final recommendation results. Another problem with TR-OREMs is that they ignore the perceived psychological reactance of consumers against the recommended products. Such consumer reactance may be reduced when the causal interrelationships among all the quantitative and qualitative factors are analyzed and incorporated properly into the OREM. To overcome these problems, we propose a causal map – online shopping recommendation mechanisms (CM-OREMs) based on a causal map. We analyzed possible causal relationships among quantitative and qualitative factors and incorporated them in the recommendation process to reduce consumer reactance against the recommendation results. Furthermore, an elaboration likelihood model (ELM) was used to build hypotheses about how the online shopping behavior of consumers is affected by OREMs based on the proposed causal map. Specifically, the performance of the proposed OREM was empirically analyzed by gathering experiment data from qualified respondents who were asked to refer to the proposed OREM before making purchasing decisions via mobile phones. Statistical results showed that the proposed OREMs could enhance consumer decision satisfaction, decision confidence, and attitude toward the recommended products. It could also positively affect consumer purchasing intentions. The OREM had a greater effect on the high-reactance group of participants than on the low-reactance group as well as on a high-involvement product versus a low-involvement product.
Online product recommendation mechanism (agents) are becoming increasingly available on websites to assist consumers with reducing information overload, provide advice in finding suitable products, and facilitate online consumer decision-making. Central of these services is consumers’ satisfaction with recommendation results. Traditional recommendation mechanism (TRM) is based content and/or collaborative filtering approach. However, the remaining problem concerning TRM is how to analyze the causal relationships between quantitative and qualitative factors, and investigate their impact on the central routes and peripheral routes through which both quantitative and qualitative factors can affect customer online shopping decisions. It is well known that qualitative factors are hard to codify yet they have a significant effect on a customer’s decision-making process in the form of causal relationships with quantitative factors. Thus, a new online recommendation mechanism is required that incorporates qualitative factors systematically with quantitative factors to analyze their combined influence on customers’ purchasing decision-making process. So, our study suggest that causal maps based recommendation mechanism (CMRM).
Knowledge is at the heart of knowledge management. In literature, a lot of studies have been suggested covering the role of knowledge in improving the performance of management. However, there are few studies about investigating knowledge itself in the arena of knowledge management. Knowledge circulating in an organization may be explicit or tacit. Until now, literature in knowledge management shows that it has mainly focused on explicit knowledge. On the other hand, tacit knowledge plays an important role in the success of knowledge management. It is relatively hard to formalize and reuse tacit knowledge. Therefore, research proposing the explication and reuse of tacit knowledge would contribute significantly to knowledge management research. In this sense, we propose using cognitive map (CM) as a main vehicle of formalizing tacit knowledge, and case-based reasoning as a tool for storing CM-driven tacit knowledge in the form of frame-typed cases, and retrieving appropriate tacit knowledge from the case base according to a new problem. Our proposed methodology was applied to a credit analysis problem in which decision-makers need tacit knowledge to assess whether a firm under consideration is healthy or not. Experiment results showed that our methodology for tacit knowledge management can provide decision makers with robust knowledge-based support.
Turbulent changes and competitive pressures have forced organizations to constantly change. Business process redesign (BPR) has been widely adopted as an organizational change method in the 1990s. Although BPR projects provide the possibility of dramatic performance improvement, many organizations have encountered serious problems due to the lack of commitment to such projects and the difficulty of systematic targeting of critical processes. By identifying the cause–effect relationships within an organization, we try to address these issues. We propose a cognitive map based method, called two-phase cognitive modeling (TCM), to help organizational members identify potential organizational conflicts, capture core business activities, and suggest ways to support the necessary organizational change. To apply the method in the real world context, we developed a prototype modeling tool, called two-phase cognitive modeling facility (TCMF). Working procedures of the TCM method and TCMF features are illustrated with their application to the real BPR project of a dairy company.
As the advent of the Internet, B2B negotiation process on the Internet has been given attention from both researchers and practitioners. Therefore, B2B ecommerce decision making will be a challenge for organizations in the foreseeable future. Some literature shows that important issues to reduce uncertainty in the development of long-term relationships among B2B commerce partners. In this sense, this paper proposes a new negotiation support system to incorporate causal relationships of negotiation terms in the process of B2B negotiation, on the basis of a cognitive map. The proposed a CAKES-NEGO (CAusal Knowledge-driven Expert System) suggests that causal relationships of negotiation terms could be explicitly represented by using the cognitive map as knowledge representation vehicle as well as inference engine. Cognitive maps can illustrate causal relationships among the factors describing a given object and/or problem, and it can also describe experts’ tacit knowledge about a certain object. A fuzzy cognitive map (FCM) is an extension of a cognitive map with the additional capability of representing feedback through weighted causal links. FCM, a fuzzy signed digraph with causal relationships between concept variables found in a specific application domain, is used for the causal knowledge acquisition. The objectives of this paper are to (1) suggest a fuzzy cognitive mapping based expert system that support decision process of decision makers and (2) apply it to the illustrative examples, which are B2B negotiation problems, to show the validity of our proposed system. In addition, statistical tests proved that the proposed negotiation mechanism could improve decision performance significantly in B2B negotiations.
A federated database system (FDBS) is a collection of cooperating database systems that are autonomous and possibly heterogeneous. In this paper, we define a reference architecture for distributed database management systems from system and schema viewpoints and show how various FDBS architectures can be developed. We then define a methodology for developing one of the popular architectures of an FDBS. Finally, we discuss critical issues related to developing and operating an FDBS.
Scientific communities have proven to be extremely successful at solving problems. They are inherently parallel systems and their macroscopic nature makes them amenable to careful study. In this paper the character of scientific research is examined drawing on sources in the philosophy and history of science. We maintain that the success of scientific research depends critically on its concurrency and pluralism. A variant of the language Ether is developed that embodies notions of concurrency necessary to emulate some of the problem solving behavior of scientific communities. Capabilities of scientific communities are discussed in parallel with simplified models of these capabilities in this language.
The authors present Pool2, a generic system for cognitive map
development and decision analysis that is based on
negative-positive-neutral (NPN) logics and NPN relations. NPN logics and
relations are extensions of two-valued crisp logic, crisp (binary)
relations, and fuzzy relations, NPN logics and relations assume logic
values in the NPN interval [-1, 1] instead of values in [0, 1]. A
theorem is presented that provides conditions for the existence and
uniqueness of heuristic transitive closures of an NPN relation. It is
shown that NPN logic and NPN relations can be used directly to model a
target world with a combination of NPN relationships of attributes
and/or concepts for the purposes of cognitive map understanding, and
decision analysis. Two algorithms are presented for heuristic transitive
closure computation and for heuristic path searching, respectively.
Basic ideas are illustrated by example. A comparison is made between
this approach and others
The early successes of computer networks in the mid-1970's made it apparent that to utilize the full potential of computer networks, international standards would be required. In 1977, the International Standards Organization (ISO) initiated work on Open Systems Interconnection (OSI) to address these requirements. This paper briefly describes the OSI Reference Model. The OSI Reference Model is the highest level of abstraction in the OSI scheme. The paper first describes the basic building blocks used to construct the network model. Then the particular seven-layer model used by OSI is briefly described, followed by a discussion of outstanding issues and future extensions for the model.
Knowledge-based systems have the potential to provide effective computer support for strategic corporate planning. Such systems are distinct from, and in some ways go beyond, the conventional financial- and mathematical-based decision support systems currently in widespread use. As part of their research in this area, the authors have developed several knowledge-based systems which are useful in strategic corporate planning. This article begins with a description of knowledge-based systems, and their distinguishing characteristics. Several areas of strategic corporate planning, which lend themselves to knowledge-based systems support, are then discussed. The article then describes a knowledge-based system for strategic corporate planning. The final section describes ways in which such systems may be expanded and developed in the future.
Considering the urgency of the need for standards which would allow constitution of heterogeneous computer networks, ISO created a new subcommittee for "Open Systems Interconnection" (ISO/ TC97/SC 16) in 1977. The first priority of subcommittee 16 was to develop an architecture for open systems interconnection which could serve as a framework for the definition of standard protocols. As a result of 18 months of studies and discussions, SC16 adopted a layered architecture comprising seven layers (Physical, Data Link, Network, Transport, Session, Presentation, and Application). In July 1979 the specifications of this architecture, established by SC16, were passed under the name of "OSI Reference Model" to Technical Committee 97 "Data Processing" along with recommendations to start officially, on this basis, a set of protocols standardization projects to cover the most urgent needs. These recommendations were adopted by T.C97 at the end of 1979 as the basis for the following development of standards for Open Systems Interconnectlon within ISO. The OSI Reference Model was also recognized by CCITT Rapporteur's Group on "Layered Model for Public Data Network Services." This paper presents the model of architecture for Open Systems Interconnection developed by SC16. Some indications are also given on the initial set of protocols which will-likely be developed in this OSI Reference Model.
The purpose of this paper is to discuss some organizational aspects of programs using the actor model of computation. In this paper we present an approach to modelling intelligence in terms of a society of communicating knowledge-based problem-solving experts. In turn each of the experts can be viewed as a society that can be further decomposed in the same way until the primitive actors of the system are reached. We are investigating the nature of the communication mechanisms needed for effective problem-solving by a society of experts and the conventions of civilized discourse that make this possible. In this way we hope eventually to develop a framework adequate for the discussion of the central issues of problem-solving involving parallel versus serial processing and centralization versus decentralization of control and information storage.This paper demonstrates how actor message passing can be used to understand control structures as patterns of passing messages in serial processing. This paper is a pre-requisite for successors which treat issues of parallelism and communication within the framework established here. The ability to analyze or synthesize any kind of control structure as a pattern of passing messages among the members of a society provides an important tool for understanding control structures. Ultimately, we hope to be able to characterize various control structures in common use by societies in terms of patterns of passing messages. This paper makes a small step in this direction by showing how to characterize familiar control structures such as iteration and recursion in these terms.
The ISO TP4 and TP0 transport layer protocols and associated network service paradigms cannot interoperate, yet both are likely to be in common use. To allow users of TP4 to communicate with users of TP0, transport layer gateways will be needed. This ...
Remote procedure calls ( RPC ) are a useful paradigm for providing communication across a network between programs written in a high level language. This paper describes a package, written as part of the Cedar project, providing a remote procedure call facility. The paper describes the options that face a designer of such a package, and the decisions we made. We describe the overall structure of our RPC mechanism, our facilities for binding RPC clients, the transport level communication protocol, and some performance measurements. We include descriptions of some optimisations we used to achieve high performance and to minimize the load on server machines that have many clients.
Our primary aim in building an RPC package was to make the building of distributed systems easier. Previous protocols were sufficiently hard to use that only members of a select group of communication experts were willing to undertake the construction of distributed systems. We hoped to overcome this by providing a communication paradigm as close as possible to the familiar facilities of our high level languages. To achieve this aim, we concentrated on making remote calls efficient, and on making the semantics of remote calls as close as possible to those of local calls.
An industrial organisation considered as a system interacts with
other systems in the course of its functioning, for greater
effectiveness. It has various subsystems such as production, marketing,
management and finance, interacting synergistically. Some systems in the
ambient environment are government, competing and collaborating
organisations, markets and society. The environment provides certain
opportunities and poses some threats. The efficacy of the organisation
depends on how well it overcomes its weaknesses and harnesses its
strengths in counteracting threats and exploiting opportunities.
Objectives set without adequate analysis of internal and external
environmental conditions are difficult to achieve. The design of a
strategic planning system, therefore, includes the function of
environmental scanning. Management faces many challenges in its quest
for effectiveness and needs to evolve a strategic master plan, conceived
of a multitude of complementary actions. The authors describe a
knowledge based system that helps set strategic objectives after giving
due weightage to both external and internal factors
The concepts of virtual agents (VAs) and virtual communities (VCs)
are proposed for interagent communication and cooperation based on
`scientific community' metaphor. VAs are `images' of autonomous agents
(expert decision support systems and human decision makers) dynamically
created in a local agent's `mind' (or knowledge base) and linked to the
remote host through attached network routines. This feature enables VAs
to be defined as network domain objects which conceal the details of
computer communications and provide an agent-oriented environment for
perspective sharing and coordination. Using this protocol, VAs can be
organized into VCs and different social protocols may be modeled as
virtual sessions in a virtual conference setting. A prototype system is
developed in C and C++ using the UDP/IP protocol. The basic ideas are
illustrated with an application example. The major advantage of this
approach lies in its utility for coordination without coercion
The author first introduces a partial taxonomy for cognitive maps
and the concepts of NPN logic and NPN relations which serve as the
theoretical basis for this work. Then, C-type neural networks are
proposed as a dynamic model for cognitive maps. Based on these models, a
distributed system, D-POOL, for cognitive map composition, derivation,
and focus generation is presented; its application to distributed group
decision support is illustrated. D-POOL first pools distributed
cognitive maps into an NPN relation which retains both negative and
positive assertions from multiple decision makers or groups in a unified
representation to gain high cognitive transparency and integrity. Then,
an NPN relation is encoded into a C-type neural model from which new
cognitive maps can be generated as decision supports from a nebulous
environment. The potential utility of the system is demonstrated by two
application examples
A partial taxonomy for cognitive maps is provided. The notions of
NPN (negative-positive-neural) logic, NPN relations, coupled-type
neurons, and coupled-type neural networks are introduced and used as a
framework for cognitive map modeling. D-POOL a cognitive-map-based
architecture for the coordination of distributed cooperative agents, is
presented. D-POOL consists of a collection of distributed nodes. Each
node is a cognitive-map-based metalevel system coupled with a local
expert/database system (or agent). To solve a problem, a local node
first pools cognitive maps from relevant agents in an NPN relation that
retains both negative and positive assertions. New cognitive maps are
then derived and focuses of attentions are generated. With the focuses,
a solution is proposed by the local node and passed to the remote
systems. The remote systems respond to the proposal, and D-POOL strives
for a cooperative or compromised solution through coherent communication
and perspective sharing. The utility of D-POOL is demonstrated using two
examples in distributed group decision support