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Reorganisation within a multi-agent system may be managed by the agents themselves by adapting the organisation to both environmental changes and their own goals. In this paper, we propose an organisation-centred model for controlling this process. Using the \(\mathcal{M}\)
oise
+ organisation model, we are able to define an organisational structur...
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... the initial organisational structure of this team is formed by five possible roles and their field area (Fig. 5). The team also has a reorganisation sub-group as defined in Sec. 3. The FS is formed by schemes that describe how to score a soccer goal. The agents missions is a set of goals associated to motor schemas that defines the robots' behaviour [9]. The team environment is composed by the match score, the match time, and the opponent. This ...
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Citations
... In our framework we explicitly look at these aspects not examined in[28]. Slightly further afield, the MOISE+ organisational framework has been used to construct organisations that act to enact organisational changes, in this case applied to a football team case study[123]. The focus is on the structural organisational elements required to re?organise an organisation. ...
... In fact, the dynamics associated to organizations have attracted the attention of the research community both from structural and a normative points of view. By structural dynamics we mean changes in the agent's populations and their relationships (Horling et al. 2001, Hübner et al. 2004, Kota et al. 2008, Dignum et al. 2005. By normative dynamics we refer to changes in regulations (Artikis et al. 2009, Campos et al. 2011. ...
Coordination infrastructures play a central role in the engineering of multiagent systems. Since the advent of agent technology, research on coordination infrastructures has produced a significant number of infrastructures with varying features. In this paper, we review the the state-of-the-art coordination infrastructures with the purpose of identifying open research challenges that next generation coordination infrastructures should address. Our analysis concludes that next generation coordination infrastructures must address a number of challenges: (i) to become
socially aware
, by facilitating human interaction within a MAS; (ii) to assist agents in their decision making by providing
decision support
that helps them reduce the scope of reasoning and facilitates the achievement of their goals; and (iii) to increase
openness
to support on-line, fully decentralised design and execution. Furthermore, we identify some promising approaches in the literature, together with the research issues worth investigating, to cope with such challenges.
... The MOISE organizational model was extended by Hübner et al. to MOISE + [68] to create an organization-centered model for independently specify the structural and functional aspects then link them by a deontic aspect. Another extension to MOISE + [69] was done to add dynamic reorganization process to adapt environment changes. ...
In complex, open, and heterogeneous environments, agents must be able to reorganize towards the most appropriate organizations to adapt unpredictable environment changes within Multi-Agent Systems (MAS). Types of reorganization can be seen from two different levels. The individual agents level (micro-level) in which an agent changes its behaviors and interactions with other agents to adapt its local environment. And the organizational level (macro-level) in which the whole system changes its structure by adding or removing agents. This chapter is dedicated to overview different aspects of what is called MAS Organization including its motivations, paradigms, models, and techniques adopted for statically or dynamically organizing agents in MAS.
... At the end of this protocol, and after all the agents in an individual way have decided about the compatibility or not with the SOX regulation of their process, the system will be in a stage in which all the agents know the results or individual decisions made by the rest of agents. There are in the literature several studies (Esteva et al. 2001; Hubner et al. 2004; Parunak and Odell 2002) showing the fact that multiagent systems need a higher level of organization to coordinate all the agents of the system. The Mutual Shared Communication Protocol proposes a parallel alternative in which all the agents share its individual findings among the rest of the agents of the system with final idea that in a further phase, all those agents together will use this shared knowledge to find a common agreed decision about the final compatibility over the full Purchasing Cycle. ...
More and more our society is linked to the stability of financial markets and this stability depends on key players like private companies, financial markets, investors, analysts, government control agencies and so on. Sarbanes-Oxley Act
is a mandatory law in EEUU market and a facto standard in rest of the world and has as main objective to keep the desire financial stability. Within this chapter it will be shown a new decision support intelligent financial model over SOX compatibility based on Artificial Intelligent technology together with Theory of Argumentation
. The main aim of this model is to help and support private companies, auditors, executive boards and regulatory bodies to take a SOX compliant decision over an specific process of a typical purchasing financial cycle: The Contracting Process. The decision will be supported by the whole argumentation process drive by this model and will be reinforce with quality measures with the final objective to create a very clear argumentative background about the suggested decision. This model directly contributes to both scientific research artificial intelligence
area and business sector. From business perspective it empowers the use of intelligent models and techniques to drive decision making over financial statements. From scientific and research area the impact is based on the combination of the following innovative elements: (1) an specific Information Seeking Dialog Protocol, (2) a Facts Valuation based Protocol in which previous gathered facts are analyzed, (3) the already incorporated initial knowledge coming from human expert knowledge, (4) the Intra-Agent Decision Making Protocol based on deductive argumentation and (5) the Semi Automated Fuzzy Dynamic Knowledge Learning Protocol giving as a result a novel approach to this kind of problems.
... This adequacy of agents and multi-agent systems applied to information fusion has been deeper discussed our previous work [39]. Open MAS [40] and virtual organizations of agents [41][42][43][44]40,45], as a specialized version of MAS, are used in this paper to allow the inclusion of organizational concepts These concepts includes rules and norms [46], groups or institutions [47] and social structures [48]. ...
... This adequacy of agents and multi-agent systems applied to information fusion has been deeper discussed our previous work [39]. Open MAS [40] and virtual organizations of agents [41][42][43][44]40,45], as a specialized version of MAS, are used in this paper to allow the inclusion of organizational concepts These concepts includes rules and norms [46], groups or institutions [47] and social structures [48]. ...
... Un exemple du premier cas se retrouve dans les travaux de [J. Hübner, J. Sichman et al., 2004], dans lesquels les agents sont capables d' évaluer leur organisation, d'identifier que le problème est causé par la définition ou spécification courante, et ainsi de décider de modifier la spécification. Ce genre de changements implique normalement des changements dans l'allocation des rôles. ...
... La décision d'initier le processus peut être soit statique, soit dynamique [J. Hübner, J. Sichman et al., 2004]. Dans le premier cas, le processus est démarré en fonc-tion de critères prédéfinis lors de la spécification de l' organisation. ...
... Moise + est un bon exemple d'une telle approche réorganisationnelle [J. Hübner, J. Sichman et al., 2004]. Ces travaux considèrent la structure (rôles, groupes) et le fonctionnement de l' organisation. ...
Les travaux présentés pour cette HDR en informatique synthétisent mes recherches dans le domaine des systèmes multi-agents (SMA), qui sont une approche de modélisation et de développement d'applications dans lesquelles, par nature, les décisions sont décentralisées, au sein d'agents. Ces agents autonomes interagissent entre eux directement ou indirectement par l'intermédiaire d'un espace partagé (appelé environnement) pour atteindre leurs objectifs individuels et collectifs. Cette approche permet d'aborder les verrous et défis ouverts par les applications actuelles, comme la décentralisation, la dynamique, le passage à l'échelle ou l'ouverture.
Dans ce cadre, nos objectifs sont de fournir des outils (méthodes et modèles) et des mécanismes (algorithmes et protocoles) de mise en place de processus d'adaptation dans de tels systèmes. Notre point de vue est que l'adaptation d'un système passe par la modification de son organisation. Je présenterai ainsi une approche qui consiste à munir les agents et le système de capacités d'auto-organisation (sans connaissance de l'état global de l'organisation) et de réorganisation (avec représentation commune de l'organisation).
Ces recherches se structurent principalement en deux axes qui sont la résolution multi-agent de problèmes et l'ingénierie orientée multi-agent. Le premier axe pose la question de l'utilisation des SMA adaptatifs pour résoudre des problèmes complexes et dynamiques. Nous proposons ici des techniques d'adaptation pour la modélisation de l'espace de recherche et d'adaptation à la dynamique environnementale des systèmes, dans le cadre de la résolution et de l'optimisation sous contraintes.
Le second axe investigue la problématique de la conception des systèmes adaptatifs, via la notion d'auto-réorganisation, dans le cadre de la programmation multi-agent. Ces travaux sont illustrés par des domaines applicatifs comme la conception aéronautique, l'intelligence ambiante et les réseaux machine-to-machine.
... That is to say, if a SOX_COMPLIANT was proposed, a SOX_COMPLIANT would be answer and if a NON_SOX_COMPLIANT was proposed, a NON_SOX_COMPLIANT would be answered (Fig. 6). At the end of this protocol, and after all the agents in an individual way have decided about the compatibility or not with the SOX regulation of their process, the system will be in a stage in which all the agents know theThere are in the literature several studies ([54] Esteva, et al., 2001;[55]Hubner,Sichman & Boissier, 2004;[56]Parunak & Odell, 2002) showing the fact that multiagent systems need a higher level of organization to coordinate all the agents of the system. The Joint Deliberative Dialogue Protocol proposes a parallel alternative in which all the agents share its individual findings among the rest of the agents of the system with final idea that in a further phase, all those agents together will use this shared knowledge to find a common agreed decision about the final compatibility over the full Purchasing Cycle. ...
The objective of this work is to define a decision support system over SOX (Sarbanes-Oxley Act) compatibility of the Imports Process based on Artificial Intelligence and Theory of Argumentation knowledge and techniques measuring at the same time the quality of how things were done on this specific process of the analyzed business case. SOX Law in effect nowadays is worldwide facto standard for financial and economical operations of private sector with the main objective to protect investors of private sector and promote the financial health of private companies. In this framework we have developed a decision support intelligent expert model to help SOX control bodies, companies and auditors to support their SOX compliance decisions based on well founded bases like Artificial Intelligence and Theory of Argumentation. The model here presented incorporates several key concepts like pre-existing expert knowledge base, a formalized and structure way to evaluate an existing business case focusing on the Imports Process, a semi automated fuzzy dynamic knowledge learning protocol and an structure method to evolve based on the facts of the business case and suggest an specific decision about the SOX compatibility of the specific business case.
... Agent organizations depend on the type of coordination and communication among agents, as well as the type of agents that comprise the group. There are several different organizational approaches [14] [13] [12][2][11] [15]. ...
Computation as interaction paradigm can be considered the most promising technological evolution in the areas of Computer Science and Communication in the last few years. Recent tendencies have conducted to the use of Virtual Organizations (VOs), which can be considered as a set of individuals and institutions that need to coordinate resources and services across institutional boundaries. Multi-agent systems (MAS) technology, which allows forming dynamic agent organizations, is particularly well suited as a support for the development of these open systems. PANGEA is an agent platform to develop open multi-agent systems, specifically those including organizational aspects such as virtual agent organizations. The platform allows the integral management of organizations and offers tools to the end user. Additionally, it includes a communication protocol based on the IRC standard, which facilitates implementation and remains robust even with a large number of connections.
... At the end of this protocol, and after all the agents in an individual way have decided about the compatibility or not with the SOX regulation of their process, the system will be in a stage in which all the agents know the results or individual decisions made by the rest of agents. There are in the literature several studies [51] Esteva, et al., 2001; [52] Hubner, Sichman & Boissier, 2004; [53] Parunak & Odell, 2002 In this section it is shown the final decision protocol in which the Multiagent System will decide if the analyzed business case is or not compatible with the SOX legislation based on the individual decisions of each of the agents of the full system. Our Multiagent System is formed by a group of agents, each one has an individual specific objective and a global group objective shared by all the agents. ...
... At the end of this protocol, and after all the agents in an individual way have decided about the compatibility or not with the SOX regulation of their process, the system will be in a stage in which all the agents know the results or individual decisions made by the rest of agents. There are in the literature several studies [51] Esteva, et al., 2001; [52] Hubner, Sichman & Boissier, 2004; [53] Parunak & Odell, 2002 In this section it is shown the final decision protocol in which the Multiagent System will decide if the analyzed business case is or not compatible with the SOX legislation based on the individual decisions of each of the agents of the full system. Our Multiagent System is formed by a group of agents, each one has an individual specific objective and a global group objective shared by all the agents. ...
The objective of this work is to define a decision support system over SOX (Sarbanes-Oxley Act) compatibility and quality of the Purchase Orders Creation Process based on Artificial Intelligence and Theory of Argumentation knowledge and techniques. This proposed model directly contributes to both scientific research artificial intelligent area and business practices. From business perspective it empowers the use of artificial intelligent models and techniques to drive decision making processes over financial statements. From scientific and research area the impact is based on the combination of 1) an Information Seeking Dialog Protocol in which a requestor agent inquires the business case; 2) a Facts Valuation based Protocol in which the previously gathered facts are analyzed; 3) the already incorporated initial knowledge of a human expert via initial beliefs; 4) the Intra-Agent Decision Making Protocol based on deductive argu-mentation; and 5) the semi automated Dynamic Knowledge Learning Protocol. Last but not least the suggested way of integration of this proposed model in a higher level multiagent intelligent system in which a Joint Deliberative Dialog Protocol and an Inter-Agent Decision Deductive Argumentation Making Protocol are described.
