Download or read book Layered Learning in Multi Agent Systems written by Peter Stone and published by . This book was released on 1998 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multi-agent systems in complex, real-time domains require agents to act effectively both autonomously and as part of a team. This dissertation addresses multi-agent systems consisting of teams of autonomous agents acting in real-time, noisy, collaborative, and adversarial environments. Because of the inherent complexity of this type of multi-agent system, this thesis investigates the use of machine learning within multi-agent systems. The dissertation makes four main contributions to the fields of Machine Learning and Multi-Agent Systems. First, the thesis defines a team member agent architecture within which a flexible team structure is presented, allowing agents to decompose the task space into flexible roles and allowing them to smoothly switch roles while acting. Team organization is achieved by the introduction of a locker-room agreement as a collection of conventions followed by all team members. It defines agent roles, team formations, and pre-compiled multi-agent plans. In addition, the team member agent architecture includes a communication paradigm for domains with single-channel, low-bandwidth, unreliable communication. The communication paradigm facilitates team coordination while being robust to lost messages and active interference from opponents. Second, the thesis introduces layered learning, a general-purpose machine learning paradigm for complex domains in which learning a mapping directly from agents' sensors to their actuators is intractable. Given a hierarchical task decomposition, layered learning allows for learning at each level of the hierarchy, with learning at each level directly affecting learning at the next higher level. Third, the thesis introduces a new multi-agent reinforcement learning algorithm, namely team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL is designed for domains in which agents cannot necessarily observe the state changes when other team members act.

Download or read book Layered Learning in Multi Agent Systems written by Peter Stone and published by . This book was released on 1998 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multi-agent systems in complex, real-time domains require agents to act effectively both autonomously and as part of a team. This dissertation addresses multi-agent systems consisting of teams of autonomous agents acting in real-time, noisy, collaborative, and adversarial environments. Because of the inherent complexity of this type of multi-agent system, this thesis investigates the use of machine learning within multi-agent systems. The dissertation makes four main contributions to the fields of Machine Learning and Multi-Agent Systems. First, the thesis defines a team member agent architecture within which a flexible team structure is presented, allowing agents to decompose the task space into flexible roles and allowing them to smoothly switch roles while acting. Team organization is achieved by the introduction of a locker-room agreement as a collection of conventions followed by all team members. It defines agent roles, team formations, and pre-compiled multi-agent plans. In addition, the team member agent architecture includes a communication paradigm for domains with single-channel, low-bandwidth, unreliable communication. The communication paradigm facilitates team coordination while being robust to lost messages and active interference from opponents. Second, the thesis introduces layered learning, a general-purpose machine learning paradigm for complex domains in which learning a mapping directly from agents' sensors to their actuators is intractable. Given a hierarchical task decomposition, layered learning allows for learning at each level of the hierarchy, with learning at each level directly affecting learning at the next higher level. Third, the thesis introduces a new multi-agent reinforcement learning algorithm, namely team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL is designed for domains in which agents cannot necessarily observe the state changes when other team members act.

Download or read book Layered Learning in Multiagent Systems written by Peter Stone and published by MIT Press. This book was released on 2000-03-03 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book looks at multiagent systems that consist of teams of autonomous agents acting in real-time, noisy, collaborative, and adversarial environments. This book looks at multiagent systems that consist of teams of autonomous agents acting in real-time, noisy, collaborative, and adversarial environments. The book makes four main contributions to the fields of machine learning and multiagent systems. First, it describes an architecture within which a flexible team structure allows member agents to decompose a task into flexible roles and to switch roles while acting. Second, it presents layered learning, a general-purpose machine-learning method for complex domains in which learning a mapping directly from agents' sensors to their actuators is intractable with existing machine-learning methods. Third, the book introduces a new multiagent reinforcement learning algorithm—team-partitioned, opaque-transition reinforcement learning (TPOT-RL)—designed for domains in which agents cannot necessarily observe the state-changes caused by other agents' actions. The final contribution is a fully functioning multiagent system that incorporates learning in a real-time, noisy domain with teammates and adversaries—a computer-simulated robotic soccer team. Peter Stone's work is the basis for the CMUnited Robotic Soccer Team, which has dominated recent RoboCup competitions. RoboCup not only helps roboticists to prove their theories in a realistic situation, but has drawn considerable public and professional attention to the field of intelligent robotics. The CMUnited team won the 1999 Stockholm simulator competition, outscoring its opponents by the rather impressive cumulative score of 110-0.

Download or read book Multi Agent Systems and Applications III written by Vladimir Marik and published by Springer Science & Business Media. This book was released on 2003-06-02 with total page 676 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the International Central and European Conference on Multi-Agent Systems, CEEMAS 2003, held in Prague, Czech Republic in June 2003. The 58 revised full papers presented together with 3 invited contributions were carefully reviewed and selected from 109 submissions. The papers are organized in topical sections on formal methods, social knowledge and meta-reasoning, negotiation, and policies, ontologies and languages, planning, coalitions, evolution and emergent behaviour, platforms, protocols, security, real-time and synchronization, industrial applications, e-business and virtual enterprises, and Web and mobile agents.

Download or read book Multi Agent Systems written by Shibakali Gupta and published by Springer Nature. This book was released on 2022-04-25 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents latest multi-agent technologies in human-centered computing (HCC) to provide a new research direction to enrich the human socio computations. Nowadays, the research in the field of multi-agent system (MAS) has gained a wide spread recognition due to its interdisciplinary nature and a vast versatile application domain including engineering, social science, economics, mathematics, operational research, etc. It has been proved that agents in MAS are the most appropriate technological paradigm for providing the most optimal solution for different kinds of complex real world problems that may be industrial or it might be specifically related to social problems. Keeping these features in mind, we planned to tune the research of latest multi-agent technologies and tried to compose its effect on HCC corridor. The primary audience of this book are research students of computer science, information technology and it will be also very helpful for software professionals to get developmental ideas to boost their computing activities.

Download or read book Multi Agent Systems for Concurrent Intelligent Design and Manufacturing written by Weiming Shen and published by CRC Press. This book was released on 2019-09-17 with total page 403 pages. Available in PDF, EPUB and Kindle. Book excerpt: Agent Technology, or Agent-Based Approaches, is a new paradigm for developing software applications. It has been hailed as 'the next significant breakthrough in software development', and 'the new revolution in software' after object technology or object-oriented programming. In this context, an agent is a computer system which is capable of act

Download or read book Architectural Design of Multi Agent Systems Technologies and Techniques written by Lin, Hong and published by IGI Global. This book was released on 2007-05-31 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book is a compilation of advanced research results in architecture and modeling issues of multi-agent systems. It serves as a reference for research on system models, architectural design languages, methods and reasoning, module interface design, and design issues"--Provided by publisher.

Download or read book Learning and Adaption in Multi Agent Systems written by Karl Tuyls and published by Springer. This book was released on 2006-03-07 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 Massively Multi Agent Systems II written by Donghui Lin and published by Springer. This book was released on 2019-05-18 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains revised selected and invited papers presented at the International Workshop on Massively Multi-Agent Systems, MMAS 2018, held in Stockholm, Sweden, in July 2018. The 7 revised full papers presented were carefully reviewed and selected for inclusion in this volume. Also included are 3 post-workshop papers. The papers discuss enabling technologies, new architectures, promising applications, and challenges of massively multi-agent systems in the era of IoT. They are organized in the following topical sections: multi-agent systems and Internet of Things; architectures for massively multi-agent systems; and applications of massively multi-agent systems.

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.

Download or read book Multiagent System Technologies written by Michael Schillo and published by Springer. This book was released on 2004-01-24 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the First German Conference on Multiagent System Technologies, MATES 2003, held in Erfurt, Germany, in September 2003. The 18 revised full papers presented together with an invited paper were carefully reviewed and selected from 49 submissions. The papers are organized in topical sections on engineering agent-based systems, systems and applications, models and architectures, the semantic Web and interoperability, and collaboration and negotiation.

Download or read book Intelligent Agents and Multi Agent Systems written by Kazuhiro Kuwabara and published by Springer Science & Business Media. This book was released on 2002-08-05 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: Autonomous agents and multi-agent systems are computational systems in which several (semi-)autonomous agents interact with each other or work together to perform some set of tasks or satisfy some set of goals. These systems may involve computational agents that are homogeneous or heterogeneous, they may involve activities on the part of agents having common or distinct goals, and they may involve participation on the part of humans and intelligent agents. This volume contains selected papers from PRIMA 2002, the 5th Paci?c Rim International Workshop on Multi-Agents, held in Tokyo, Japan, on August 18–19, 2002 in conjunction with the 7th Paci?c Rim International Conference on Arti?cial Intelligence (PRICAI-02). PRIMA is a series of workshops on - tonomous agents and multi-agent systems, integrating activities in the Asian and Paci?c Rim countries. PRIMA 2002 built on the great success of its pre- cessors, PRIMA’98 in Singapore, PRIMA’99 in Kyoto, Japan, PRIMA 2000 in Melbourne, Australia, and PRIMA 2001 in Taipei, Taiwan. We received 35 submissions to this workshop from 10 countries. Each paper was reviewed by three internationally renowned program committee members. After careful reviews, 15 papers were selected for this volume. We would like to thank all the authors who submitted papers to the workshop. We would also like to thank all the program committee members for their splendid work in reviewing the papers. Finally, we thank the editorial sta? of Springer-Verlag for publishing this volume in the Lecture Notes in Arti?cial Intelligence.

Download or read book Principles of Practice in Multi Agent Systems written by Jung-Jin Yang and published by Springer. This book was released on 2009-12-15 with total page 671 pages. Available in PDF, EPUB and Kindle. Book excerpt: Agents are software processes that perceive and act in an environment, processing their perceptions to make intelligent decisions about actions to achieve their goals. Multi-agent systems have multiple agents that work in the same environment to achieve either joint or conflicting goals. Agent computing and technology is an exciting, emerging paradigm expected to play a key role in many society-changing practices from disaster response to manufacturing to agriculture. Agent and mul- agent researchers are focused on building working systems that bring together a broad range of technical areas from market theory to software engineering to user interfaces. Agent systems are expected to operate in real-world environments, with all the challenges complex environments present. After 11 successful PRIMA workshops/conferences (Pacific-Rim International Conference/Workshop on Multi-Agents), PRIMA became a new conference titled “International Conference on Principles of Practice in Multi-Agent Systems” in 2009. With over 100 submissions, an acceptance rate for full papers of 25% and 50% for posters, a demonstration session, an industry track, a RoboCup competition and workshops and tutorials, PRIMA has become an important venue for multi-agent research. Papers submitted are from all parts of the world, though with a higher representation of Pacific Rim countries than other major multi-agent research forums. This volume presents 34 high-quality and exciting technical papers on multimedia research and an additional 18 poster papers that give brief views on exciting research.

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 Multiagent Systems second edition written by Gerhard Weiss and published by MIT Press. This book was released on 2016-10-28 with total page 917 pages. Available in PDF, EPUB and Kindle. Book excerpt: The new edition of an introduction to multiagent systems that captures the state of the art in both theory and practice, suitable as textbook or reference. Multiagent systems are made up of multiple interacting intelligent agents—computational entities to some degree autonomous and able to cooperate, compete, communicate, act flexibly, and exercise control over their behavior within the frame of their objectives. They are the enabling technology for a wide range of advanced applications relying on distributed and parallel processing of data, information, and knowledge relevant in domains ranging from industrial manufacturing to e-commerce to health care. This book offers a state-of-the-art introduction to multiagent systems, covering the field in both breadth and depth, and treating both theory and practice. It is suitable for classroom use or independent study. This second edition has been completely revised, capturing the tremendous developments in multiagent systems since the first edition appeared in 1999. Sixteen of the book's seventeen chapters were written for this edition; all chapters are by leaders in the field, with each author contributing to the broad base of knowledge and experience on which the book rests. The book covers basic concepts of computational agency from the perspective of both individual agents and agent organizations; communication among agents; coordination among agents; distributed cognition; development and engineering of multiagent systems; and background knowledge in logics and game theory. Each chapter includes references, many illustrations and examples, and exercises of varying degrees of difficulty. The chapters and the overall book are designed to be self-contained and understandable without additional material. Supplemental resources are available on the book's Web site. Contributors Rafael Bordini, Felix Brandt, Amit Chopra, Vincent Conitzer, Virginia Dignum, Jürgen Dix, Ed Durfee, Edith Elkind, Ulle Endriss, Alessandro Farinelli, Shaheen Fatima, Michael Fisher, Nicholas R. Jennings, Kevin Leyton-Brown, Evangelos Markakis, Lin Padgham, Julian Padget, Iyad Rahwan, Talal Rahwan, Alex Rogers, Jordi Sabater-Mir, Yoav Shoham, Munindar P. Singh, Kagan Tumer, Karl Tuyls, Wiebe van der Hoek, Laurent Vercouter, Meritxell Vinyals, Michael Winikoff, Michael Wooldridge, Shlomo Zilberstein

Download or read book Multi agent Systems for Traffic and Transportation Engineering written by and published by IGI Global. This book was released on 2009-01-01 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book aims at giving a complete panorama of the active and promising crossing area between traffic engineering and multi-agent system addressing both current status and challenging new ideas"--Provided by publisher.

Download or read book Multi Agent Systems and Applications written by Michael Luck and published by Springer Science & Business Media. This book was released on 2001-06-20 with total page 1366 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents selected tutorial lectures given at the summer school on Multi-Agent Systems and Their Applications held in Prague, Czech Republic, in July 2001 under the sponsorship of ECCAI and Agent Link. The 20 lectures by leading researchers in the field presented in the book give a competent state-of-the-art account of research and development in the field of multi-agent systems and advanced applications. The book offers parts on foundations of MAS; social behaviour, meta-reasoning, and learning; and applications.