Download or read book Adaptive Agents and Multi Agent Systems II written by Daniel Kudenko and published by Springer Science & Business Media. This book was released on 2005-03-04 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive agents and multi-agent systems is an emerging and exciting interdisciplinary area of research and development involving artificial intelligence, software engineering, and developmental biology, as well as cognitive and social science. This book presents 17 revised and carefully reviewed papers taken from two workshops on the topic as well as 2 invited papers by leading researchers in the area. The papers deal with various aspects of machine learning, adaptation, and evolution in the context of agent systems and autonomous agents.
Download or read book Adaptive Agents and Multi Agent Systems written by Eduardo Alonso and published by Springer Science & Business Media. This book was released on 2003-04-23 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Adaptive Agents and Multi Agent Systems III Adaptation and Multi Agent Learning written by Karl Tuyls and published by Springer. This book was released on 2008-02-09 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Adaptive Agents and Multi Agent Systems II written by Daniel Kudenko and published by Springer. This book was released on 2009-09-02 with total page 313 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive agents and multi-agent systems is an emerging and exciting interdisciplinary area of research and development involving artificial intelligence, software engineering, and developmental biology, as well as cognitive and social science. This book presents 17 revised and carefully reviewed papers taken from two workshops on the topic as well as 2 invited papers by leading researchers in the area. The papers deal with various aspects of machine learning, adaptation, and evolution in the context of agent systems and autonomous agents.
Download or read book Adaptive Agents and Multi Agent Systems written by Eduardo Alonso and published by Springer. This book was released on 2014-03-12 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Learning and Adaption in Multi Agent Systems written by Karl Tuyls and published by Springer Science & Business Media. This book was released on 2006-04-10 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-proceedings of the First International Workshop on Learning and Adaption in Multi-Agent Systems, LAMAS 2005, held in The Netherlands, in July 2005, as an associated event of AAMAS 2005. The 13 revised papers presented together with two invited talks were carefully reviewed and selected from the lectures given at the workshop.
Download or read book Adaption and Learning in Multi agent Systems written by Gerhard Weiss and published by . This book was released on 1996 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book is based on the workshop on Adaptation and Learning in Multi-Agent Systems, held in conjunction with the International Joint Conference on Artificial Intelligence, IJCAI'95, in Montreal, Canada in August 1995. The 14 thoroughly reviewed revised papers reflect the whole scope of current aspects in the field: they describe and analyze, both experimentally and theoretically, new learning and adaption approaches for situations in which several agents have to cooperate or compete. Also included, and aimed at the novice reader, are a comprehensive introductory survey on the area with 154 references listed and a subject index. As the first book solely devoted to this area, this volume documents the state of the art and is thus indispensable for anyone active or interested in the field."--PUBLISHER'S WEBSITE.
Download or read book Adaptive and Learning Agents written by Peter Vrancx and published by Springer Science & Business Media. This book was released on 2012-03-09 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the thoroughly refereed post-conference proceedings of the International Workshop on Adaptive and Learning Agents, ALA 2011, held at the 10th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2011, in Taipei, Taiwan, in May 2011. The 7 revised full papers presented together with 1 invited talk were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on single and multi-agent reinforcement learning, supervised multiagent learning, adaptation and learning in dynamic environments, learning trust and reputation, minority games and agent coordination.
Download or read book Adaptation and Learning in Multi Agent Systems written by Gerhard Weiss and published by . This book was released on 2014-01-15 with total page 580 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Design of Intelligent Multi Agent Systems written by Rajiv Khosla and published by Springer Science & Business Media. This book was released on 2004-10-05 with total page 476 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is a tremendous interest in the design and applications of agents in virtually every area including avionics, business, internet, engineering, health sciences and management. There is no agreed one definition of an agent but we can define an agent as a computer program that autonomously or semi-autonomously acts on behalf of the user. In the last five years transition of intelligent systems research in general and agent based research in particular from a laboratory environment into the real world has resulted in the emergence of several phenomenon. These trends can be placed in three catego ries, namely, humanization, architectures and learning and adapta tion. These phenomena are distinct from the traditional logic centered approach associated with the agent paradigm. Humaniza tion of agents can be understood among other aspects, in terms of the semantics quality of design of agents. The need to humanize agents is to allow practitioners and users to make more effective use of this technology. It relates to the semantic quality of the agent design. Further, context-awareness is another aspect which has as sumed importance in the light of ubiquitous computing and ambi ent intelligence. The widespread and varied use of agents on the other hand has cre ated a need for agent-based software development frameworks and design patterns as well architectures for situated interaction, nego tiation, e-commerce, e-business and informational retrieval. Fi- vi Preface nally, traditional agent designs did not incorporate human-like abilities of learning and adaptation.
Download or read book Autonomous Agents and Multi agent Systems written by Jiming Liu and published by World Scientific. This book was released on 2001 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. Contents: Behavioral Modeling, Planning, and Learning; Synthetic Autonomy; Dynamics of Distributed Computation; Self-Organized Autonomy in Multi-Agent Systems; Autonomy-Oriented Computation; Dynamics and Complexity of Autonomy-Oriented Computation. Readership: Undergraduate and graduate students in computer science and most engineering disciplines, as well as computer scientists, engineers, researchers and practitioners in the field of machine intelligence.
Download or read book Adaptive Learning Agents written by Matthew E. Taylor and published by Springer Science & Business Media. This book was released on 2010-03-24 with total page 149 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the thoroughly refereed post-conference proceedings of the Second Workshop on Adaptive and Learning Agents, ALA 2009, held as part of the AAMAS 2009 conference in Budapest, Hungary, in May 2009. The 8 revised full papers presented were carefully reviewed and selected from numerous submissions. They cover a variety of themes: single and multi-agent reinforcement learning, the evolution and emergence of cooperation in agent systems, sensor networks and coordination in multi-resource job scheduling.
Download or read book Organizational Learning and Network Adaptation in Multi agent Systems written by Matthew E. Gaston and published by . This book was released on 2005 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Innovations in Multi Agent Systems and Application 1 written by Dipti Srinivasan and published by Springer Science & Business Media. This book was released on 2010-08-10 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of multi-agent systems and several applications that have been developed for real-world problems. Multi-agent systems is an area of distributed artificial intelligence that emphasizes the joint behaviors of agents with some degree of autonomy and the complexities arising from their interactions. Multi-agent systems allow the subproblems of a constraint satisfaction problem to be subcontracted to different problem solving agents with their own interest and goals. This increases the speed, creates parallelism and reduces the risk of system collapse on a single point of failure. Different multi-agent architectures, that are tailor-made for a specific application are possible. They are able to synergistically combine the various computational intelligent techniques for attaining a superior performance. This gives an opportunity for bringing the advantages of various techniques into a single framework. It also provides the freedom to model the behavior of the system to be as competitive or coordinating, each having its own advantages and disadvantages.
Download or read book Adaptive Agents and Multi Agent Systems III Adaptation and Multi Agent Learning written by Karl Tuyls and published by Springer Science & Business Media. This book was released on 2008-02-08 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Adaptive Agents and Multi agent Systems III Adaptation and Multi agent Learning written by and published by . This book was released on 2008 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Rollout Policy Iteration and Distributed Reinforcement Learning written by Dimitri Bertsekas and published by Athena Scientific. This book was released on 2021-08-20 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this book is to develop in greater depth some of the methods from the author's Reinforcement Learning and Optimal Control recently published textbook (Athena Scientific, 2019). In particular, we present new research, relating to systems involving multiple agents, partitioned architectures, and distributed asynchronous computation. We pay special attention to the contexts of dynamic programming/policy iteration and control theory/model predictive control. We also discuss in some detail the application of the methodology to challenging discrete/combinatorial optimization problems, such as routing, scheduling, assignment, and mixed integer programming, including the use of neural network approximations within these contexts. The book focuses on the fundamental idea of policy iteration, i.e., start from some policy, and successively generate one or more improved policies. If just one improved policy is generated, this is called rollout, which, based on broad and consistent computational experience, appears to be one of the most versatile and reliable of all reinforcement learning methods. In this book, rollout algorithms are developed for both discrete deterministic and stochastic DP problems, and the development of distributed implementations in both multiagent and multiprocessor settings, aiming to take advantage of parallelism. Approximate policy iteration is more ambitious than rollout, but it is a strictly off-line method, and it is generally far more computationally intensive. This motivates the use of parallel and distributed computation. One of the purposes of the monograph is to discuss distributed (possibly asynchronous) methods that relate to rollout and policy iteration, both in the context of an exact and an approximate implementation involving neural networks or other approximation architectures. Much of the new research is inspired by the remarkable AlphaZero chess program, where policy iteration, value and policy networks, approximate lookahead minimization, and parallel computation all play an important role.
