We use here reactive multi-agent systems a self-organized and decentralized approachfor problem solving. We study how reactive agents, acting only according to their localperceptions, can produce robust and competitive performance. So, getting formal proofs ofthe system's properties is an important issue to be taken care of. In particular, we evaluatethe interest of these kind o...

MOTIVATION During task composition, such as can be found in distributed query processing, workflow systems and AI planning, decisions have to be made by the system and possibly by users with respect to how a given problem should be solved. Although there is often more than one correct way of solving a given problem, these multiple solutions do not necessarily lead to the same result. Some resea...

The manufacturing sector has been facing major challenges as it undergoes revolutionary changes fuelled by new and sophisticated demands from customers, global competition, distribution of manufacturing and marketing activities, and technological advances. In order to address these challenges, manufacturing enterprises need to change the way they do business and adopt innovative organizational ...

Coordination of Communication in Robot Teams by Reinforcement Learning p. 156 Self-organized Multi-agent System for Robot Deployment in Unknown Environments p. 165 Selective Method Based on Auctions for Map Inspection by Robotic Teams p. 175 Study of a Multi-Robot Collaborative Task through Reinforcement Learning p. 185 Design of Social Agents p. 192 Event-Based System for Generation of Traffic...

In this paper, we present a prototype for our solution called Data Exchange Autonomic Manager (DEAM) [1] which has as main goal to turn Data Exchange processes into selfmanaged systems. We believe that providing data exchange processes with self-healing autonomic capability is a promising approach toward reliable self-managed and resilient data exchange processes. We describe the high level arc...