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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.
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
This book contains selected and revised papers of the European Symposium on Adaptive and Learning Agents and Multi-Agent Systems (ALAMAS), editions 2005, 2006 and 2007, held in Paris, Brussels and Maastricht. The goal of the ALAMAS symposia, and this associated book, is to increase awareness and interest in adaptation and learning for single agents and mul- agent systems, and encourage collaboration between machine learning experts, softwareengineeringexperts,mathematicians,biologistsandphysicists,andgive a representative overviewof current state of a?airs in this area. It is an inclusive forum where researchers can present recent work and discuss their newest ideas for a ?rst time with their peers. Thesymposiaseriesfocusesonallaspectsofadaptiveandlearningagentsand multi-agent systems, with a particular emphasis on how to modify established learning techniques and/or create new learning paradigms to address the many challenges presented by complex real-world problems. These symposia were a great success and provided a forum for the pres- tation of new ideas and results bearing on the conception of adaptation and learning for single agents and multi-agent systems. Over these three editions we received 51 submissions, of which 17 were carefully selected, including one invited paper of this year’s invited speaker Simon Parsons. This is a very c- petitive acceptance rate of approximately 31%, which, together with two review cycles, has led to a high-quality LNAI volume. We hope that our readers will be inspired by the papers included in this volume.
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 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
This book constitutes the proceedings of the 14th German Conference on Multiagent System Technologies, MATES 2016, held in Klagenfurt, Austria, in September 2016. 12 long papers and 5 short papers were carefully reviewed and selected from 28 submissions. MATES 2016 conference talks covered a broad area of topics of interest including MAS engineering and modeling, issues of human-agent interaction, collaboration and coordination, agent-based adaptation and optimization, and applications of MAS, in particular in the smart energy domain.
"This book provide a comprehensive view of current developments in agent organizations as a paradigm for both the modeling of human organizations, and for designing effective artificial organizations"--Provided by publisher.
This book constitutes the refereed proceedings of the 4th International Conference on Industrial Applications of Holonic and Multi-Agent Systems, HoloMAS 2009, held in Linz, Austria, August 31 - September 2, 2009. The 31 revised full papers presented were carefully reviewed and selected from 47 submissions. The papers are organized in topical sections on introduction & motivation, knowledge-centered approaches, selected theoretical aspects, MAS scheduling & simulation, holonic systems for manufacturing, and MAS & holonic applications.
Today’s IT systems with its ever-growing communication infrastructures and computing applications are becoming more and more large in scale, which results in exponential complexity in their engineering, operation and maintenance. Recently, it has widely been recognized that self-organization and self-management / regulation offer the most promising approach to addressing such challenges. Self-organization and adaptation are concepts stemming from the nature and have been adopted in systems theory. They are considered to be the essential ingredients of any living organism and, as such, are studied intensively in biology, sociology and organizational theory. They have also penetrated into control theory, cybernetics and the study of adaptive complex systems. Computing and communication systems are basically artificial systems. This prevents conventional self-organization and adaptation principles and approaches from being directly applicable to computing and communication systems. The methodology of multi-agent systems and the technology of Grid computing have shed lights for the exploration into the self-organization and adaptation of large-scale complex IT systems. This book provides in-depth thoughts about the above discussed challenges as well as a range of state-of-the-art methodologies and technologies for the entirely new area. We refer to this newly emerging area as Self-Organization and Autonomic Informatics, which has represented the future generation of IT systems, comprised of communication infrastructures and computing applications, which are inherently large-scale, complex and open.
Building research grade multi-agent systems usually involves a broad variety of software infrastructure ingredients like planning, scheduling, coordination, communication, transport, simulation, and module integration technologies and as such constitutes a great challenge to the individual researcher active in the area. The book presents a collection of papers on approaches that will help make deployed and large scale multi-agent systems a reality. The first part focuses on available infrastructure and requirements for constructing research-grade agents and multi-agent systems. The second part deals with support in infrastructure and software development methods for multi-agent systems that can directly support coordination and management of large multi-agent communities; performance analysis and scalability techniques are needed to promote deployment of multi-agent systems to professionals in software engineering and information technology.