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... What I suggest and what the videos exemplify is different as it attempts to acknowledge complexity as a helpful, productive and healthy element in artistic and educational encounters. The said complexity facilitates linkage between the evaluation of internal demand and external opportunity and consequently helps a divergent frame of mind; that is, an acceptance that we can integrate constructively into multiple and at times contradictory discourses (luca;pErronE, 2001). ...
... What I suggest and what the videos exemplify is different as it attempts to acknowledge complexity as a helpful, productive and healthy element in artistic and educational encounters. The said complexity facilitates linkage between the evaluation of internal demand and external opportunity and consequently helps a divergent frame of mind; that is, an acceptance that we can integrate constructively into multiple and at times contradictory discourses (luca;pErronE, 2001). ...
Resumo
The aim of this article is to create a link between critical attributes to meaningful educational change and the kind of learning and thinking that is facilitated by artistic endeavors. The goal is not to simply advocate for the Arts, but rather to present a doorway to an educational practice that can be used in educational thought in general. The article starts from David McCarthy’s (2000) proposition that “we must think possibility within constraint; that is the condition of our time” (150), arguing that the kinds of thought experiences that individuals ‘doing art’ participate in, can serve as a model for educational thinking, particularly given the complexity, volatility and speed realities of a 21st century education.
... In the traditional approach, mathematics has been the main tool of analysis, but it can only deal with simple analytically tractable models with homogeneous, perfectly rational agents. For the new paradigm, computational and numerical methods have become an important tool of analysis, with agent-based simulation models supported by more and more powerful computational technology (Judd and Tesfatsion 2005; Johnson et al 2003; Luna and Perrone 2002). Very recently LeBaron reviewed agent-based financial market models (Judd and Tesfatsion 2005). ...
... In the traditional approach, mathematics has been the main tool of analysis, but it can only deal with simple analytically tractable models with homogeneous, perfectly rational agents. For the new paradigm, computational and numerical methods have become an important tool of analysis, with agent-based simulation models supported by more and more powerful computational technology (Judd and Tesfatsion 2005;Johnson et al 2003;Luna and Perrone 2002). Very recently LeBaron reviewed agent-based financial market models (Judd and Tesfatsion 2005). ...
This paper studies the simulation of financial markets using an agent-based mix-game model which is a variant of the minority game (MG). It specifies the spectra of parameters of mix-game models that fit financial markets by investigating the dynamic behaviors of mix-game models under a wide range of parameters. The main findings are (a) in order to approach efficiency, agents in a real financial market must be heterogeneous, boundedly rational and subject to asymmetric information; (b) an active financial market must be dominated by agents who play a minority game; otherwise, the market would die; (c) the system could be stable if agents who play a majority game have a faster learning rate than those who play a minority game; otherwise, the system could be unstable. The paper then induces the rules for simulating financial markets with mix-game models and gives an example. Finally, the appendix of this paper presents background information about \'El Farol bar\', MG and mix-games.
... В статье Омара Герреро и Роберта Акстелля подробно анализируется такой системный метод (Axtell, Guerrero, 2011). С прикладными исследовательскими областями применения агент-ориентированного моделирования можно ознакомиться, например, в работах (Luna, Perrone, 2002;D'Orazio, Silvestri, 2014). ...
The article discusses the evolution of two approaches to using computer simulations in economic research. The first was created by the American mathematician Norbert Wiener, who used the theory of cybernetics as a method of scientific research and cognition. The second, which also began its journey in the period 1944–1955, is based on the writings of John von Neumann, then a consultant to Los Alamos National Laboratory, and his invention of cellular automata. The first section provides an overview of the Wiener path, which became the guiding reference point for the Forrester system dynamics and Orcutt microsimulations. The second section presents the Neumann path, which gave birth to such methods as Monte Carlo and agent-based modeling, which, as a result, through the efforts of G. Epstein and P. Axtel, was transformed into a conceptual approach of artificial life specifically designed for socio-economic experiments. Finally, the third section explores the potential for developing hybrid simulations by combining the methods of the two paths in concern.
... Network organizations, such as businesses and schools, have used spherical thinking to find new metaphors to frame plans of action. Only recently, however, has sphericity linked the evaluation of internal demand and external opportunity to understandings of coadunationthat is, the constructive collaboration of multiple and, at times, contradictory discourses-and simultaneity (Luca and Perrone 2001;Miles and Snow 1995). This new way of thinking implies that internal relations are directly connected to external possibilities, but, more important, that these associations are more than simplistic structures of hierarchy and cause and effect. ...
If policy is the most significant gatekeeping element for access to and development of community goods and services, and if music educators have historically lived at the margins of policy, then who procures access for the field? How are visions for musical and educational development articulated and what are the resulting implications? This article suggests sphericity as a metaphorical point of entry in discussing the need for the music education field to consider policy and policy studies differently. The article argues for connections between policy and teacher education, contending that the practice of contesting and creating representations of knowledge structures and learning based on deliberative skills is at the center of policy formation and development, as well as the center of teaching.
... Brahms is unique by combining a Subsumption-based BDIlanguage with an BDI-based Agent Simulation Language (see section Activity Subsumption Architecture below). In contrast, Swarm (Minar, Burkhart, & Langton, 1996), an often-used language for modelling and simulating social and economic behaviour of large agent societies (Luna & Perrone, 2002), is not based on any particular theory of human behaviour and is not an agent modelling language in the strict sense. Rather, Swarm extends an imperative language in the form of object libraries for Objective-C (an object-oriented programming language) (Terna, 1998). ...
Modelling and simulating work processes is often done at such an abstract level that individual work practice - collaboration, communication, 'off-task' behaviours, multi-tasking, interrupted and resumed activities, informal interactions, use of tools and movements - is left out, making the description of how the work in an organisation actually gets done impossible. This paper describes the Brahms modelling and simulation environment, developed at NASA Ames Research Center. The Brahms modelling language is geared towards modelling people's activity behaviour, making it an ideal environment for simulating organisational processes at a level that allows the analysis of the work practice and designing new work processes at the implementation level.
... How ACE can avoid "the tower of Babel effect" by people stealing code from each other is discussed inBruun(2002). ...
... and used by a growing community of social scientists. For descriptions and applications of Swarm to economic phenomena, see[44],[31], and[30]. For all the details describing the ID prototype structure, see also[43]. ...
Industrial districts (IDs) are complex inter-organizational systems based on an evolutionary network of interactions among
heterogeneous, localized, functionally integrated and complementary firms. With an agent-based prototype, we explore how cognitive
processes and social reflexivity dynamics of ID firms affect technological adaptation and economic performance of ID as a
whole. Rather than observing IDs just by the point of view of the so-called bottom-up emerging properties, we try to study
how firms develop over time “districtualized” behavioral attitudes, through cognitive capabilities of typifying and contextualizing
in a social sense their technological, organizational and economic action. The question is: do cognitive processes, like those
mentioned, have a great impact on technological learning and economic performance of firms over time?
... Without translating this advantage into empirical contexts, the applied value of ABM remains limited and the focus remains on hypothetical and theoretical analyses. The framework for and describing different parameterisation sequences should also be tested in various modelling (Janssen and Ostrom, 2006; Robinson et al., 2007) and other application contexts (Matthews et al., 2007) such as the growing domain of Social Epidemiology in public health research (Kaplan, 2004) or agent-based economics (Luna and Perrone, 2002). Further refinement and testing of this framework would allow for reducing model uncertainty, for provision of systematic guidelines for building and applying empirical ABMs, and for facilitation of the model comparisons (Parker et al., 2008a,b). ...
Agent-based modelling has become an important tool to investigate socio-ecological processes. Its use is partially driven by increasing demand from decision makers to provide support for understanding the potential implications of decisions in complex situations. While one of the advantages of agent-based modelling is the ability to simulate the implications of human decision-making processes explicitly, methods for providing empirical support for the representation of the behaviour of human agents have not been structured systematically. This paper develops a framework for the parameterisation of human behaviour in agent-based models and develops twelve distinct sequences for the characterisation and parameterisation of human behaviours. Examples are provided to illustrate the most important sequences. This framework is a first step towards a guide for parameterisation of human behaviour in ABM. A structured discussion within the agent-based community is needed to achieve a more definitive guideline.
... We use Swarm [5] as programming language to simulate the model, and then analyze the dynamic and evolutionary process of corruption on various numerical variables and parameters. As discussed above, there are two types of Agent, i.e. ...
The aim of this paper is to gain the broad explanation of corruption using simple computational model. We elaborated further the model of corruption described previously in (4), with some additions in model's properties. We performed hundreds of experiments computationally using Swarm and constructed the explanation of corruption based upon these results. We show that corruption should be understood as complex social-phenomena, which relates not only with economical aspect, but also with many other social and anthropological aspects.
... *) See Luna, et. al (2002), for more examples on Swarm. The G-agent will interact with P-Agent and decides whether or not she agrees to corrupt The G-Agent who chooses to corrupt will have the probability of getting busted. The G-agent will calculate the expectation value based on her subjective thought, honesty index and jail term as described in previous sectio ...
The aim of this paper is to gain the broad explanation of corruption using simple computational model. We elaborated further the model of corruption described previously in Situngkir (2003b), with some additions in model’s properties. We performed hundreds of experiments computationally using Swarm and constructed the explanation of corruption based upon these results. We show that corruption should be understood as complex social-phenomena, which relates not only with economical aspect, but also with many other social and anthropological aspects.
... A new volume is now appearing (Luna and Perrone, 2001), that continues the development, with Swarm, of this kind of agent based applications to economics and finance 7 . ...
There are three different symbol systems available to social scientists: the familiar verbal argumentation and mathematics, but also a third way, computer simulation. Computer simulation, or computational modeling involves representing a model as a computer program. The key question is: What tools can we use in building our models, if we follow the third way ? Simulation will have to be written in some Esperanto: it is obvious that the current Babel is against the emergence of a renewed enthusiastic effort in economic theory. Swarm is a library of functions offering tools in the middle between basic programming (Fortran, C, C++, Java) and closed packages for dynamic simulation; it helps us to develop our own software, using a well-defined protocol and powerful tools to deal with agents' behavior, interaction and time sequences.So it can be considered an excellent candidate to play the role of simulation's Esperanto. Swarm will break the main barrier preventing a complete diffusion of these techniques, i.e. the necessity of being able to write code, to assemble it, to look for bugs etc. with a substantial advance in spreading the knowledge emerging from artificial experiments and simulation.
Program trading originates from combination trading technology in 70's in America. It was popular, but once it was considered as root of disaster. Nowadays, there are many divergences on program trading risk in international academic world. This essay is to analyze program trading on risk of stock market. The method adopts computational experiment to build artificial stock market under various experimental conditions. The research will consider two strategies: combination insurance strategy and arbitrage strategy to inspect stock index futures' influences on artificial stock market. Through contrast experiments, it finds that program trading will cause abnormal fluctuation of stock market in short-term period but it will have slight impact on fluctuation of stock market in long-term period. On the whole, stock index futures reduce price fluctuation of spot market. Besides, the research finds that combination insurance strategy will increase short selling expectation in pessimistic market to accelerate market collapse when the market gives the same downside price expectation and the market should consider the influence of combination insurance strategy.
Exploiting a precise reproduction of a stock exchange, the robustness of the continuous double auction (CDA) mechanism, evaluated by means of the waiting time distributions, has been proved versus 36 different setups made by varying both the operators' behavior and the market micro structure. The obtained results demonstrate that the CDA remains able to clear strongly different order flows, although the Milan stock exchange seemed to be a little more efficient than the NYSE under the allocative point of view, evidencing the intrinsic complexity of the stock market. The simulation has been built as an agent-based model in order to obtain a plausible order flow. The decisions of single agents and their interaction through the market book are realistic and reproduce some empirical analysis results. The mentioned results have been obtained either by the analysis of the complete pending time series or the same computation of the asks and bids series alone.
The education of software engineering students more and more addresses enterprise-oriented organizational and management issues, like for instance modeling the business structure and environment of the enterprise which will receive a new software system. The teaching of business modeling technologies based on standards like UML and the Rational Unified Process raises novel questions that need to be addressed. Business modeling consists in modeling organizations and their workflows; in several cases the modeling can be complemented by business simulation. This paper presents as a case study some Agent-Based Simulation tools for modeling the enterprise dynamics, and shows how we exploited them to teach an Organizational Software Engineering laboratory course, providing students with Software Engineering skills along with Agent-Based Simulation principles.
Industrial ecological system is a sustainable mode of modern industry development. Industrial symbiosis, a sub-field of industrial ecology, engages traditionally separate industries in a collective approach, involving exchange of materials, energy, water, and/or by-products, to enhance competitive ability and environmental performance. To construct a symbiosis analysis method, this article employs a number of parameters embodying information about materials, energy and economics as the main essential parameters in system analysis and introduces symbiosis profit and symbiotic consumption elements as the economic indicators. A modeling and simulation program is designed using the agent-based modeling approach to simulate the evolvement of a hypothetical coal-based industrial system and the change of symbiosis conditions in the process of construction is examined. The simulation program built using the Swarm library, which is a freely available multi-agent simulation package, provides a useful demonstration for the symbiosis analysis method.
Given simple agent rules, a swarm's emergent behavior can be difficult to predict. The inverse problem is even more difficult: Given a desired emergent behavior, what are the rules by which swarm agents should operate? Disjunctive fuzzy control is proposed as a method to model swarm agents. Compared to more commonly used conjunctive fuzzy control such as that proposed by Mamdani, disjunctive fuzzy control is robustly fault tolerant and disjointly connected. Swarms are inherently disjunctive. Instead of agents working in coordination with one another, each swarm agent contributes individually to the result. The disjunctive attribute can also be applied at the sensor level for each individual agent. Disjunctive control allows adaptation of the describing membership function, as is commonly done in conjunctive control. The inversion process is illustrated with numerous simulation examples, including a predator-prey game, gang warfare, and escaping agents. The swarm is instructed what to do but not how to do it. Imposition of fitness constraints and repeated generations of evolutionary molding of agent performance can then result in unexpected emergent behaviors of the swarm, e.g., use of decoys, self-sacrifice, flanking maneuvers, and shielding of the weak.
Nonlinear tools and concepts (derived from the relatively recent computational advances in the physical, biological, and cognitive sciences) offer valuable insights into the evolution and behavior of human as well as natural systems. Hence, of late, organizational studies have begun to apply both the methods, as well as the metaphors, of nonlinear dynamical systems (known by the popular terms “chaos” and “complexity”). While these various studies often allude to unique epistemological features, full-blown theoretical developments are rare indeed. Moreover, this lack of a coherent foundation leads to a number of misconceptions, not the least of which is the belief that the results of nonlinear analysis can be integrated easily with existing social theories. In reality they present significant theoretical challenges. Specifically, they rely upon its concepts of holism and emergence, as well as alternative perspectives of sociocultural evolution and collective rationality. Thus, serious theory building requires a revival of elements from earlier Systems Theories, including the development of certain hybrid concepts such as “Systemic Choice” (which seeks to reconcile human agency and institutional processes).
This paper gives an overview of the Nigeria's recent experience on corruption in the context of economic reforms programme. It discusses the possible causes and effects of corruption, which are seen to be rooted in socio-cultural practices and the political and economic situation of the country. Data were drawn chiefly from news stories, reports of tribunals and commissions of enquiry, interviews of Nigerians with relevant information, anecdotes, and personal knowledge of Nigeria. The results of the study show that there have been significant reductions in the level of corruption in the country through the introduction of government anti-corruption instruments. In addition, this study found a negative correlation between levels of corruption and economic growth thereby making it difficult for Nigeria to develop fast. In Nigeria, corruptions stifle economic growth; reduce economic efficiency and development despite the enormous resources in the country. Corruption creates negative national image and loss of much needed revenue. It devalues the quality of human life, robs schools, agricultural sectors, hospital and welfare services of funds. It discourages foreign investments leading to decrease in Foreign Direct Investment. It exacerbates inequality, desecrates the rule of law and undermines the legitimacy and stability of democratic regimes. It slows down administrative processes thereby making the implementation of government reforms policies ineffective. People engage in corrupt practices in Nigeria as a result of high level of poverty, high unemployment rate, under-remuneration of workers, financial hardship, persuasion by friends and colleagues in public offices, desire to please kinsmen, late payment of contractors by government, over-concentration of power and resources at the center, unregulated informal economy, nepotism, tribalism in the administration of justice and lack of honest leaders. The biggest challenge for the country therefore is not just to punish corrupt behaviour or go into bargaining plea. The country must reverse the prevailing culture in which corruption is viewed as permissible. People should be educated on the dangers of excessive materialism and the culture of 'get rich quick'. There is also the need for more job creation with better remuneration.
The paper aims to describe an agent-based prototype that has been created to investigate the relation among local labour markets, entrepreneurship and human capital in IDs. It basically describes the building blocks of the prototype, the agents acting in it and the forces that drive its most interesting dynamics. Some interesting hypotheses to investigate are sketched, too.
Recent years have seen a proliferation of Multi-agent-based simulation (MABSS) models, in a growing range of domains, and
using an increasing variety of software. In this article we compare some Agent Based environments anyone can download in Internet.
The aim of this article is to discuss the general principles of each environment, and not to say which is the best or the
worst one. The comparison is performed along several dimensions such as ease of learning, flexibility, available support,
etc. It should also help the choice of a language by potential practitioners of agent-based economic. At the end of this article
there’s a personal proposition about these environments of the author.
In this paper we follow an “evolutionary approach” to solve the “Busy Beaver Game” using agent based techniques. In 1962 Tibor Rado proposed one function based on what is known today as the “Busy Beaver Game or Problem”. The question Rado asked was: Suppose a Turing Machine (TM) with a two ways infinite tape and a tape alphabet ={0,1}. What is the maximum number of 1’s that can be written by an N-State (N does not include the final state) halting TM when started on a blank tape? This number, which is function of the number of states, is denoted by Σ(N). A machine that produces Σ(N) non-blank cells is called a Busy Beaver (BB). The problem with Σ(N) is that it grows faster than any computable function, i.e., Σ(N) is non computable. Some values for Σ(N), and the corresponding TM’s are known today for small values of N, as described in the following table. As the number of states increases the problem becomes harder, and, for n≥5, there are some “theoretical” candidates (or contenders) which set lower bounds on the value of Σ(N).
En esta tesis doctoral demostramos que la simulación y el modelado basado en agentes constituyen una aproximación metodológica robusta y rigurosa para abordar la complejidad multidimensional de la gestión del agua doméstica en áreas metropolitanas emergentes. En particular, integramos y adaptamos diferentes submodelos sociales –de dinámicas urbanas, de difusión tecnológica y de opinión, y de consumo de agua– en un modelo basado en agentes que a su vez enlazamos con un sistema de información geográfico. El resultado es un entorno computacional programado para realizar la simulación de políticas de demanda de agua en distintos escenarios. Hemos parametrizado el modelo general en la Región Metropolitana de Valladolid obteniendo interesantes resultados. Las conclusiones obtenidas de esta forma son difícilmente alcanzables por otra vía, empleando por ejemplo las técnicas convencionales de previsión. Mostramos de esta forma que la metodología descrita es capaz de complementar aquéllas ofreciendo visiones alternativas, realistas y rigurosas del problema. _______________________________ In this doctoral thesis we demonstrate that the combination of agent based modelling and simulation is a robust and rigorous methodological approach for dealing with the multidimensional complexity of freshwater management in emergent metropolitan areas. In particular, we integrate and adapt different social submodels –models of urban dynamics, water consumption, and technological and opinion diffusion– in an agent based model that is, in turn, linked with a geographic information system (GIS). The result is a computational environment that enables the simulation and comparison of various water demand policies under different scenarios. We have successfully parameterized the general model for the Metropolitan Area of Valladolid, obtaining interesting results. The conclusions drawn in this way would have been difficult to obtain using other approaches, such as conventional forecasting methods. We prove that the described methodology can complement conventional approaches, offering realistic and rigorous alternative insights to the problem.
In this paper, we extend the Solow growth model to include corruption as a determinant of the multifactor productivity using a Cobb-Douglas production function framework. In addition to the classical components of any growth model (output, labor, capital), we incorporate corruption as a determinant of government expenditure, investment and foreign aid. It is proposed that output and growth are influenced by the level of corruption. This model is to be tested empirically to trace the corruptive behaviour in Lebanon based on the available time series data.
The complexity of the acute inflammatory response (AIR) is, by now, generally recognized. The primary manifestation of this property has been the difficulty in translating the information derived from reductionist, basic science research into effective clinical treatment regimens for sepsis. However, the recognition of the "complexity" of the AIR is not without its pitfalls. Despite its limitations, reductionism remains the primary means of obtaining scientific information. Furthermore, a functional shortcoming of use of the term complex has been to make it equivalent to "essentially unsolvable." Therefore, a mechanism is needed to integrate the apparatus of reductionist analysis into a complex synthetic methodology that overcomes the current limitations of both. Toward this end, I propose a structure for a class of collaborative, community-wide in silico models that use the framework of agent-based modeling. Agent-based modeling is a type of mathematical modeling that focuses on the behaviors of the components of complex systems and is well suited for translating the results of basic science experiments. I will also introduce a preliminary version of a syntactical "grammar" that can potentially be used to facilitate the transfer of basic science data into computer code. It is hoped that when a mature version of this framework is implemented, the resulting models will provide a functional, synthetic data base on the AIR that could be used for directing research, testing hypotheses, teaching and training, and drug discovery/testing.
Since Tibor Rado in 1962 defined the busy beaver game, several approaches have used computer technology to search for 'best' candidates to solve it. In this paper we follow an 'evolutionary approach' to solving it using agent-based techniques. This approach includes techniques to reduce the number of inspected Turing machines and to accelerate simulation of Turing machines using agent-based techniques; in particular we use the 'Swarm simulation toolkit'. Our approach uses a variety of learning techniques such as genetic algorithms, classifier systems multiple genetic algorithms and random search to explore the universe of the 'best solution' to the game. Copyright Blackwell Publishing Ltd 2004.
This paper analyses the primary features of computing intelligence in the circumstance of multi-agents modeling, and the artificial cognitive methods with computing intelligent agents, and the artificial cognitive features in reinforcement learning and the Q-routing algorithm which is a kind of reinforcement learning in the domain of intelligent network. At the same time, aiming at the problem in AntNet routing algorithm, this paper introduces BP-CT ant routing algorithm and simulates the algorithm on OMNeT++ software platform, then proves the availability of the algorithm. Considering the global planning and optimal control theory, BP-CT ant routing algorithm has some potential aspects of intelligent control, and shows good QoS performance.
Work systems involve people engaging in activities over time-not just with each other, but also with machines, tools, documents, and other artifacts. These activities often produce goods, services, or-as is the case in the work system described in this article-scientific data. Work systems and work practice evolve slowly over time. The integration and use of technology, the distribution and collocation of people, organizational roles and procedures, and the facilities where the work occurs largely determine this evolution.
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