Download or read book Evolutionary Multi Agent Systems written by Aleksander Byrski and published by Springer. This book was released on 2016-12-21 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses agent-based computing, concentrating in particular on evolutionary multi-agent systems (EMAS), which have been developed since 1996 at the AGH University of Science and Technology in Cracow, Poland. It provides the relevant background information on and a detailed description of this computing paradigm, along with key experimental results. Readers will benefit from the insightful discussion, which primarily concerns the efficient implementation of computing frameworks for developing EMAS and similar computing systems, as well as a detailed formal model. Theoretical deliberations demonstrating that computing with EMAS always helps to find the optimal solution are also included, rounding out the coverage.
Download or read book Coevolutionary Computation and Multiagent Systems written by Li-cheng Jiao and published by WIT Press. This book was released on 2012 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: The origins of evolutionary computation can be traced back to the late 1950's where it remained, almost unknown, to the broader scientific community for three decades until the 1980's when it started to receive significant attention, as did the study of multi-agent systems (MAS). This focuses on systems in which many intelligent agents interact with each other. Today these systems are not simply a research topic but are also beginning to become an important subject of academic teaching and industrial and commercial application. Co-Evolutionary Computational and Multi-Agent Systems introduces the author's recent work in these two new and important branches of artificial intelligence.
Download or read book Multi Agent Applications with Evolutionary Computation and Biologically Inspired Technologies Intelligent Techniques for Ubiquity and Optimization written by Chen, Shu-Heng and published by IGI Global. This book was released on 2010-07-31 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book compiles numerous ongoing projects and research efforts in the design of agents in light of recent development in neurocognitive science and quantum physics, providing readers with interdisciplinary applications of multi-agents systems, ranging from economics to engineering"--Provided by publisher.
Download or read book Agent Based Evolutionary Search written by Ruhul A. Sarker and published by Springer Science & Business Media. This book was released on 2010-07-12 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: Agent based evolutionary search is an emerging paradigm in computational int- ligence offering the potential to conceptualize and solve a variety of complex problems such as currency trading, production planning, disaster response m- agement, business process management etc. There has been a significant growth in the number of publications related to the development and applications of agent based systems in recent years which has prompted special issues of journals and dedicated sessions in premier conferences. The notion of an agent with its ability to sense, learn and act autonomously - lows the development of a plethora of efficient algorithms to deal with complex problems. This notion of an agent differs significantly from a restrictive definition of a solution in an evolutionary algorithm and opens up the possibility to model and capture emergent behavior of complex systems through a natural age- oriented decomposition of the problem space. While this flexibility of represen- tion offered by agent based systems is widely acknowledged, they need to be - signed for specific purposes capturing the right level of details and description. This edited volume is aimed to provide the readers with a brief background of agent based evolutionary search, recent developments and studies dealing with various levels of information abstraction and applications of agent based evo- tionary systems. There are 12 peer reviewed chapters in this book authored by d- tinguished researchers who have shared their experience and findings spanning across a wide range of applications.
Download or read book Evolutionary Models in Multi agent Systems written by and published by . This book was released on 1997 with total page 97 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 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 Evolution Through Reputation written by Nikolaos Chatzinikolaou and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Little attention has been paid, in depth, to the relationship between fitness evaluation in evolutionary algorithms and reputation mechanisms in multi-agent systems, but if these could be related it opens the way for implementation of distributed evolutionary systems via multi-agent architectures. Our investigation concentrates on the effectiveness with which social selection, in the form of reputation, can replace direct fitness observation as the selection bias in an evolutionary multi-agent system. We do this in two stages: In the first, we implement a peer-to-peer, adaptive Genetic Algorithm (GA), in which agents act as individual GAs that, in turn, evolve dynamically themselves in real-time, using the traditional evolutionary operators of fitness-based selection, crossover and mutation. In the second stage, we replace the fitness-based selection operator with a reputation-based one, in which agents choose their mates based on the collective past experiences of themselves and their peers. Our investigation shows that this simple model of distributed reputation can be successful as the evolutionary drive in such a system, exhibiting practically identical performance and scalability to direct fitness observation. Further, we discuss the effect of noise (in the form of "defective" agents) in both models. We show that the reputation-based model is significantly better at identifying the defective agents, thus showing an increased level of resistance to noise.
Download or read book Evolutionary Computation in Multi Agent Systems written by Claudio Bonacina and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 Agent Based Evolutionary Search written by Ruhul A. Sarker and published by Springer. This book was released on 2010-06-09 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: Agent based evolutionary search is an emerging paradigm in computational int- ligence offering the potential to conceptualize and solve a variety of complex problems such as currency trading, production planning, disaster response m- agement, business process management etc. There has been a significant growth in the number of publications related to the development and applications of agent based systems in recent years which has prompted special issues of journals and dedicated sessions in premier conferences. The notion of an agent with its ability to sense, learn and act autonomously - lows the development of a plethora of efficient algorithms to deal with complex problems. This notion of an agent differs significantly from a restrictive definition of a solution in an evolutionary algorithm and opens up the possibility to model and capture emergent behavior of complex systems through a natural age- oriented decomposition of the problem space. While this flexibility of represen- tion offered by agent based systems is widely acknowledged, they need to be - signed for specific purposes capturing the right level of details and description. This edited volume is aimed to provide the readers with a brief background of agent based evolutionary search, recent developments and studies dealing with various levels of information abstraction and applications of agent based evo- tionary systems. There are 12 peer reviewed chapters in this book authored by d- tinguished researchers who have shared their experience and findings spanning across a wide range of applications.
Download or read book Intelligent Agents in the Evolution of Web and Applications written by Ngoc Thanh Nguyen and published by Springer Science & Business Media. This book was released on 2009-01-17 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent agents have revolutionised the way we do business, we teach, we learn, design systems, and so on. Agent applications are increasingly being developed in - mains as diverse as meteorology, manufacturing, war gaming, UAV mission mana- ment and the evolution of Web [1]. The Web has also has the same effect on our daily life as the intelligent agents. We use Web for information search, shopping, news, communication and so on. We wonder how we lived without Web in the past [2]. The book presents a sample of some of the most innovative research on the use of intelligent agents in the evolution of Web. There are thirteen chapters in the book. Chapters are on theoretical foundations as well as practical applications. We are grateful to the contributors and reviewers for their contribution. We believe that the research reported in the book will encourage researchers to develop the robust human-like intelligent machines for the service of humans. We sincerely thank Springer-Verlag for their editorial support during the prepa- tion of the manuscript. The editors appreciate the resources provided by Wroclaw University of Technology and the University of South Australia to edit this volume.
Download or read book Innovations in Multi Agent Systems and Application 1 written by Dipti Srinivasan and published by Springer. This book was released on 2010-07-17 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: In today’s world, the increasing requirement for emulating the behavior of real-world applications for achieving effective management and control has necessitated the usage of advanced computational techniques. Computational intelligence-based techniques that combine a variety of problem solvers are becoming increasingly pervasive. The ability of these methods to adapt to the dynamically changing environment and learn in an online manner has increased their usefulness in simulating intelligent behaviors as observed in humans. These intelligent systems are able to handle the stochastic and uncertain nature of the real-world problems. Application domains requiring interaction of people or organizations with different, even possibly conflicting goals and proprietary information handling are growing exponentially. To efficiently handle these types of complex interactions, distributed problem solving systems like multiagent systems have become a necessity. The rapid advancements in network communication technologies have provided the platform for successful implementation of such intelligent agent-based problem solvers. An agent can be viewed as a self-contained, concurrently executing thread of control that encapsulates some state and communicates with its environment, and possibly other agents via message passing. Agent-based systems offer advantages when independently developed components must interoperate in a heterogenous environment. Such agent-based systems are increasingly being applied in a wide range of areas including telecommunications, Business process modeling, computer games, distributed system control and robot systems.
Download or read book Adaptive Agents and Multi Agent Systems II written by Daniel Kudenko and published by Springer. This book was released on 2005-02-18 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 Evolutionary and Conventional Reinforcement Learning in Multi Agent Systems for Social Simulation written by Luis Miramontes Hercog and published by . This book was released on 2003 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Evolvability of Multi Agent Systems written by and published by . This book was released on 2006 with total page 3 pages. Available in PDF, EPUB and Kindle. Book excerpt: The goal of this research was to analyze and improve the learning process for multi-agent systems using evolutionary algorithms (EAs). In particular, we wanted to take advantage of our previous work in developing a set of tools for analyzing the evolvability of genetic operators using Price's equation (Price 1970), a theory borrowed from the population genetics community. All of our previous work with Price's equation (Potter, et.al. 2003; Bassett et.al. 2004) has been done on very traditional EA representations, specifically vectors of real values. Part of our research was to focus on how to adapt the use of Price's equation to a representation appropriate for controlling agents in a multi- agent environment. We chose to look at rule-based representations, in part because there are a large number of genetic operators defined for this representation that could be analyzed. Another part of the research was to involve building multi-agent problem domains that could be used for testing our learning algorithms.
Download or read book Multiagent Robotic Systems written by Jiming Liu and published by CRC Press. This book was released on 2018-10-08 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing a guided tour of the pioneering work and major technical issues, Multiagent Robotic Systems addresses learning and adaptation in decentralized autonomous robots. Its systematic examination demonstrates the interrelationships between the autonomy of individual robots and the emerged global behavior properties of a group performing a cooperative task. The author also includes descriptions of the essential building blocks of the architecture of autonomous mobile robots with respect to their requirement on local behavioral conditioning and group behavioral evolution. After reading this book you will be able to fully appreciate the strengths and usefulness of various approaches in the development and application of multiagent robotic systems. It covers: Why and how to develop and experimentally test the computational mechanisms for learning and evolving sensory-motor control behaviors in autonomous robots How to design and develop evolutionary algorithm-based group behavioral learning mechanisms for the optimal emergence of group behaviors How to enable group robots to converge to a finite number of desirable task states through group learning What are the effects of the local learning mechanisms on the emergent global behaviors How to use decentralized, self-organizing autonomous robots to perform cooperative tasks in an unknown environment Earlier works have focused primarily on how to navigate in a spatially unknown environment, given certain predefined motion behaviors. What is missing, however, is an in-depth look at the important issues on how to effectively obtain such behaviors in group robots and how to enable behavioral learning and adaptation at the group level. Multiagent Robotic Systems examines the key methodological issues and gives you an understanding of the underlying computational models and techniques for multiagent systems.
