Multi-agent reinforcement learning (RL) solves the problem of how each agent should
behave optimally in a stochastic environment in which multiple agents are learning …

Artificial Intelligence (AI) has emphasized building\stand-alone systems" that can solve
problems with minimal help from other systems (computer or human). These systems have …

By studying current research into agents the people have selected the following types of
agent as the basis for spatial agent development: mobile agents, interface agents …

Advanced modeling techniques are a necessary tool in order to design and manage
manufacturing systems effectively. This book contains a set of tutorial chapters on topics …

In this chapter, we show how artificial intelligence (AI) can be applied to the study of
organizations. Specifically, we construct an AI model of a small organization in which …

The investigation of the collective dynamics of multi-agent systems in terms of the study of
the properties of single agents is not feasible when the number of interacting agents is large …

Le cadre de travail dans lequel s' inscrit cette thèse porte sur le développement d'une
structure de pilotage prenant en compte simultanément les contraintes prévisionnelles et les …

The aim of this paper is to point out some of the abilities of Distributed Artificial Intelligence in
the domain of scheduling, control and design support of Flexible Manufacturing Systems. A …

Research in multiagent systems (MAS), or distributed artificial intelligence (DAI), dates back
to the late 1970s. Initial work in the area focused on distributed interpretation of sensor data …

Business process and workflows represent diagrams as Business Process Model Language
(BPML), Unified Model Language (UML), which may contain errors made by a designer. In …