Agentes y sistemas multiagente : Modelos teóricos y aplicaciones

Este artículo describe en forma resumida los trabajos de investigación y desarrollo que se están llevando a cabo en la línea de Agentes y Sistemas Multiagente del Laboratorio de Investigación y Desarrollo en Inteligencia Computacional (LIDIC) de la Universidad Nacional de San Luis. Los principales enfoques abordados en esta línea de investigación fueron presentados en el WICC2003 [5]. Se continúa ahora con el estado de avance y los resultados obtenidos recientemente con la utilizaci´on de estos enfoques. Si bien este artículo constituye una breve síntesis de los trabajos realizados y en ejecución, intentará reflejar las principales temáticas abordadas para posibilitar un intercambio de experiencias con otros investigadores participantes del Workshop, que trabajen sobre líneas de investigación afines. El artículo está organizado alrededor de dos grandes ítems: modelos teóricos y aplicaciones. En el primer caso, se describen los estudios y desarrollos realizados con modelos teóricos de agentes y sistemas multiagente. En las aplicaciones se presentan las principales conclusiones de las experiencias logradas con el diseño e implementación de sistemas basados en estos paradigmas.Eje: Inteligencia artificial distribuida, aspectos teóricos de la inteligencia artificial y teoría de computaciónRed de Universidades con Carreras en Informática (RedUNCI

Agentes y sistemas multiagente : Modelos teóricos y aplicaciones

Este artículo describe en forma resumida los trabajos de investigación y desarrollo que se están llevando a cabo en la línea de Agentes y Sistemas Multiagente del Laboratorio de Investigación y Desarrollo en Inteligencia Computacional (LIDIC) de la Universidad Nacional de San Luis. Los principales enfoques abordados en esta línea de investigación fueron presentados en el WICC2003 [5]. Se continúa ahora con el estado de avance y los resultados obtenidos recientemente con la utilizaci´on de estos enfoques. Si bien este artículo constituye una breve síntesis de los trabajos realizados y en ejecución, intentará reflejar las principales temáticas abordadas para posibilitar un intercambio de experiencias con otros investigadores participantes del Workshop, que trabajen sobre líneas de investigación afines. El artículo está organizado alrededor de dos grandes ítems: modelos teóricos y aplicaciones. En el primer caso, se describen los estudios y desarrollos realizados con modelos teóricos de agentes y sistemas multiagente. En las aplicaciones se presentan las principales conclusiones de las experiencias logradas con el diseño e implementación de sistemas basados en estos paradigmas.Eje: Inteligencia artificial distribuida, aspectos teóricos de la inteligencia artificial y teoría de computaciónRed de Universidades con Carreras en Informática (RedUNCI

Algorithms for finding coalitions exploiting a new reciprocity condition

We introduce a reciprocity criterion for coalition formation among goal-directed agents, which we call the indecomposable do-ut-des property. It refines an older reciprocity property, called the do-ut-des or give-to-get property by considering the fact that agents prefer to form coalitions whose components cannot be formed independently. A formal description of this property is provided as well as an analysis of algorithms and their complexity. We provide an algorithm to decide whether a coalition has the desired property, and we show that the problem to verify whether a single coalition satisfies the property is tractable. Moreover, we provide an algorithm to search all the sub-coalitions of a given coalition satisfying the new property. Even if this problem is not computationally tractable, we show that in several cases, also the complexity of this problem may decrease considerably

An extended process automation system : an approach based on a multi-agent system

This thesis describes studies on application of multi-agent systems (acronym: MAS) to enhance process automation systems. A specification of an extended process automation system is presented. According to this specification, MAS can be used to extend the functionality of ordinary process automation systems at higher levels of control. Anticipated benefits of the specification include enhanced reconfigurability, responsiveness and flexibility properties of process automation. Previous research concerning applications of MAS in process automation has been more limited than in other fields of automation. There has been more research about this topic for example in the area of discrete manufacturing. As goal-oriented distributed systems with coordination capabilities MAS have been found applicable to a part of automation functions, e.g. modification of control logic in abnormal situations. However, when applying MAS to process automation the particular characteristics of this application domain need to be taken into account. The important role of continuous control in process automation needs to be considered. In this thesis, a specification of an agent platform for process automation is presented as a basis for applying MAS in this application domain. The specification extends a FIPA-compliant agent platform with process automation specific functionality. It utilises a hierarchical agent organisation, a BDI-agent model and qualitative reasoning. It also presents a model for programming MAS applications for process automation with techniques of distributed planning and search. Two applications are specified using the platform. One of these shows how the techniques of distributed planning can be applied in sequential control. The other provides a design model for supervisory continuous control applications using the techniques of distributed search. Experiments performed with a laboratory test environment using prototype implementations of the applications are presented. The experiments are able to demonstrate the feasibility of the approach in limited test scenarios. They also provide information about in which ways MAS techniques are able enhance the properties of process automation. As a result of the work presented in this thesis more knowledge has been gained about application of MAS in process automation. The specification of the agent platform for process automation and its applications provide a basis for further studies of this topic.reviewe

Méthodologie de développement de systèmes multi-agents adaptatifs et conception de logiciels à fonctionnalité émergente

Environments within which applications are embedded are growing in complexity and dynamicity, considering the large number and the diversity of the takeholders. Functions of such systems become more and more difficult to define, and their specifications are often incomplete, even if their components are easily identifiable and specifiable. Without new design and modeling methods, managing such project will become too constraining, long and costly to cope with.We propose to use cooperative self-organising adaptive multi-agent systems (AMAS) to tackle these design problems. The functionality of such systems emerges from coopera- tive interactions between agents. Nevertheless, developing using AMAS is still an ad-hoc process and reduced to a small group of users. Several applications have been designed by using AMAS, but it has never been executed by novices and non AMAS experts. To answer to this lack of visibility and openess, the ADELFE project – for Atelier de DEveloppement de Logiciels à Fonctionnalité Emergente or Toolkit for developing applications with emergent functionalities – proposes to develop a methodology based on these emergence oriented principles. This methodology is defined in three points : process, notations and tools. The ADELFE process is based on the Rational Unified Process and extends or adds some agent specific activities. Notations are extensions of UML and A-UML. Tools have been developed or extended in to support notations, with OpenTool, and following the process is eased by using AdelfeToolkit.The relevance of this approach has been confronted to the development of experimental applications. Some results from a dynamic timetable solver, ETTO, and from a multi-robot transportation task are presented and analysed.Les environnements des applications d’aujourd’hui sont de plus en plus complexes et dy- namiques, compte tenu du grand nombre et de la diversité des acteurs en jeu. Les fonctions de tels systèmes deviennent alors de plus en plus difficiles à définir, et leur spécification est souvent incomplète, même si les composantes restent pleinement identifiables et spécifiables. Si de nouvelles méthodes de conception et de modélisation ne sont pas mises au point, la gestion des projets deviendra de plus en plus contraignante, longue et coûteuse.Nous proposons d’utiliser les systèmes multi-agents adaptatifs par auto-organisation coopérative pour palier ces problèmes de conception. La fonctionnalité de ces systèmes est une résultante émergeant des interactions coopératives entre agents. Toutefois, le développement de tels systèmes est resté confidentiel et réduit à un groupe autour de ses créateurs directs. Certes de nombreuses applications ont été conçues grâce à ces systèmes, mais jamais par des novices, non experts du domaine. Pour répondre à ce manque de visibilité et d’ouverture, le projet ADELFE - pour Atelier de DEveloppement de Logiciels à Fonctionnalité Emergente - propose de développer une méthode de développement d’applications repo- sant sur ces principes et définie en trois points : un processus, des notations et des outils. Le processus d’ADELFE est basé sur le Rational Unified Process et y ajoute des activités spécifiques à l’ingénierie orientée agent. Les notations sont une extension des notations UML et A-UML. Des outils ont été développés ou étendus afin de prendre en charge à la fois les notations, grâce à OpenTool, et le processus, grâce à un outil d’aide au suivi appelé AdelfeToolkit.La pertinence de cette méthodologie a été mise à l’épreuve au cours de développements d’applications diverses. Nous présentons ici les résultats obtenus pour un problème de résolution dynamique d’emploi du temps, ETTO (pour Emergent Time Tabling Organisation), et pour un problème de transport multi-robot de ressources

Role-based and agent-oriented teamwork modeling

Teamwork has become increasingly important in many disciplines. To support teamwork in dynamic and complex domains, a teamwork programming language and a teamwork architecture are important for specifying the knowledge of teamwork and for interpreting the knowledge of teamwork and then driving agents to interact with the domains. Psychological studies on teamwork have also shown that team members in an effective team often maintain shared mental models so that they can have mutual expectation on each other. However, existing agent/teamwork programming languages cannot explicitly express the mental states underlying teamwork, and existing representation of the shared mental models are inefficient and further become an obstacle to support effective teamwork. To address these issues, we have developed a teamwork programming language called Role-Based MALLET (RoB-MALLET) which has rich expressivity to explicitly specify the mental states underlying teamwork. By using roles and role variables, the knowledge of team processes is specified in terms of conceptual notions, instead of specific agents and agent variables, allowing joint intentions to be formed and this knowledge to be reused by different teams of agents. Further, based on roles and role variables, we have developed mechanisms of task decomposition and task delegation, by which the knowledge of a team process is decomposed into the knowledge of a team process for individuals and then delegate it to agents. We have also developed an efficient representation of shared mental models called Role-Based Shared Mental Model (RoB-SMM) by which agents only maintain individual processes complementary with others?? individual process and a low level of overlapping called team organizations. Based on RoB-SMMs, we have developed tworeasoning mechanisms to improve team performance, including Role-Based Proactive Information Exchange (RoB-PIE) and Role-Based Proactive Helping Behaivors (RoBPHB). Through RoB-PIE, agents can anticipate other agents?? information needs and proactively exchange information with them. Through RoB-PHB, agents can identify other agents?? help needs and proactively initialize actions to help them. Our experiments have shown that RoB-MALLET is flexible in specifying reusable plans, RoB-SMMs is efficient in supporting effective teamwork, and RoB-PHB improves team performance