Organized Adaption In Multi Agent Systems
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Organized Adaption in Multi-Agent Systems
Adaptation, for purposes of self-healing, self-protection, self-management, or self-regulation, is currently considered to be one of the most challenging pr- erties of distributed systems that operate in dynamic, unpredictable, and - tentially hostile environments. Engineering for adaptation is particularly c- plicated when the distributed system itself is composed of autonomous entities that, on one hand, may act collaboratively and with benevolence, and, on the other,maybehavesel?shlywhilepursuingtheirowninterests.Still,theseentities have to coordinate themselves in order to adapt appropriately to the prevailing environmental conditions, and furthermore, to deliberate upon their own and the system’s con?guration, and to be transparent to their users yet consistent with any human requirements. The question, therefore, of “how to organize the envisagedadaptationforsuchautonomousentitiesinasystematicway”becomes of paramount importance. The ?rst international workshop on “Organized Adaptation in Multi-Agent Systems” (OAMAS) was a one-day event held as part of the workshop p- gram arranged by the international conference on Autonomous Agents and Multi-Agent Systems (AAMAS). It was hosted in Estoril during May, 2008, and was attended by more than 30 researchers. OAMAS was the steady convergence of a number of lines of research which suggested that such a workshop would be timely and opportune. This includes the areas of autonomic computing, swarm intelligence, agent societies, self-organizing complex systems, and ‘emergence’ in general.
Autonomous Agents And Multi-agent Systems: Explorations In Learning, Self-organization And Adaptive Computation
An autonomous agent is a computational system that acquires sensory data from its environment and decides by itself how to relate the external stimulus to its behaviors in order to attain certain goals. Responding to different stimuli received from its task environment, the agent may select and exhibit different behavioral patterns. The behavioral patterns may be carefully predefined or dynamically acquired by the agent based on some learning and adaptation mechanism(s). In order to achieve structural flexibility, reliability through redundancy, adaptability, and reconfigurability in real-world tasks, some researchers have started to address the issue of multiagent cooperation. Broadly speaking, the power of autonomous agents lies in their ability to deal with unpredictable, dynamically changing environments. Agent-based systems are becoming one of the most important computer technologies, holding out many promises for solving real-world problems.The aims of this book are to provide a guided tour to the pioneering work and the major technical issues in agent research, and to give an in-depth discussion on the computational mechanisms for behavioral engineering in autonomous agents. Through a systematic examination, the book attempts to provide the general design principles for building autonomous agents and the analytical tools for modeling the emerged behavioral properties of a multiagent system.
Adaptive Agents and Multi-Agent Systems
Author: Eduardo Alonso
language: en
Publisher: Springer Science & Business Media
Release Date: 2003-04-23
Adaptive Agents and Multi-Agent Systems is an emerging and exciting interdisciplinary area of research and development involving artificial intelligence, computer science, software engineering, and developmental biology, as well as cognitive and social science. This book surveys the state of the art in this emerging field by drawing together thoroughly selected reviewed papers from two related workshops; as well as papers by leading researchers specifically solicited for this book. The articles are organized into topical sections on - learning, cooperation, and communication - emergence and evolution in multi-agent systems - theoretical foundations of adaptive agents