PLENARY CONFERENCES

IBERAMIA 2004
Noviembre 22-26
Tonantzintla - Puebla - México

Contact: iberamia2004@inaoep.mx






Multi-Agent Systems: a way of thinking intelligence collectively

Abstract: Multi-agent systems (MAS) are a wide field of research at the junction of several other fields in computer science (such as artificial intelligence, software engineering and distributed systems) and also other fields outside of computer science like biology, social science, or business science.

MAS is today, indisputably, a suitable paradigm to build intelligent systems where: 1) the basic entities, modelled as agents, have local information or capabilities for solving the problems and, thus, have only a partial view; 2) both the control and the knowledge of the system are decentralised (intrinsically or for efficiency and robustness reasons); and 3) the computation is asynchronous and potentially distributed among a network of computers (e.g. WEB applications, telecommunication software, diagnostic programs or medical applications, etc. ).

The agents are considered to be autonomous entities (e.g. ants, robots, drones, etc.). Their interactions lie within either cooperative or competitive behaviours. That is, the agents can share a common goal (cooperative agents), or they can pursue their own interests (self-interested or competitive agents).

This talk will focus on MAS as a cognitive approach that helps developing distributed, cooperative and intelligent systems where intelligence is built collectively among agents. It is structured around three main aspects of MAS:

  1. Cognition refers to intelligent skills of agents (autonomy, learning, planning, reasoning, etc.) and endows agents with reflexive behaviour, i.e. agents can act, observe and control autonomously their actions.
  2. Interaction allows agents, viewed as intelligent and autonomous entities, to exchange their knowledge (or beliefs), to solve potential conflicts or to enhance synergy between their activities. Interaction is the basic mechanism that supports more sophisticated ones such as coordination, negotiation or consensus reaching.
  3. Concurrency enables the agents to achieve distributed tasks both in cooperative and competitive cases. Concurrency provides the essential and well established mechanisms (e.g. synchronous or asynchronous communications, distributed observation, mobility, etc.) that support the effective running of distributed MAS.

This talk will also outline the main domains of applications where MAS technology brings an added-value while building distributed and cooperative intelligent systems. The whole concepts and mechanisms presented in this talk will be illustrated through two industrial applications we developed in the domain of Aircraft simulation and Telecommunication.

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