Balancing Reactivity And Social Deliberation In Multi Agent Systems
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Balancing Reactivity and Social Deliberation in Multi-Agent Systems by Markus Hannebauer,Jan Wendler,Enrico Pagello Pdf
This book presents a subselection of papers presented at the ECAI 2000 Workshop on Balancing Reactivity and Social Deliberation in Multi-Agent Systems together with additional papers from well-known researchers in the field. The 13 revised full papers were carefully reviewed and selected for inclusion in the present book. Besides two introductory survey papers, the book offers topical sections on architectures and frameworks, enhanced reactivity, and controlled social deliberation.
Balancing Reactivity and Social Deliberation in Multi-Agent Systems by Markus Hannebauer,Jan Wendler,Enrico Pagello Pdf
This book presents a subselection of papers presented at the ECAI 2000 Workshop on Balancing Reactivity and Social Deliberation in Multi-Agent Systems together with additional papers from well-known researchers in the field. The 13 revised full papers were carefully reviewed and selected for inclusion in the present book. Besides two introductory survey papers, the book offers topical sections on architectures and frameworks, enhanced reactivity, and controlled social deliberation.
Adaptive Agents and Multi-Agent Systems by Eduardo Alonso,Daniel Kudenko,Dimitar Kazakov Pdf
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
Regulated Agent-Based Social Systems by Gabriela Lindemann,Daniel Moldt,Mario Paolucci Pdf
This book presents selected extended and reviewed versions of the papers accepted for the First International Workshop on Regulated Agent Systems: Theory and Applications, RASTA 2002, held in Bologna, Italy, in July 2002, as part of AAMAS 2002. In addition, several new papers on the workshop theme are included as well; these were submitted and reviewed in response to a further call for contributions. The construction of artificial agent societies deals with questions and problems that are already known from human societies. The 16 papers in this book establish an interdisciplinary community of social scientists and computer scientists devoting their research interests to exploiting social theories for the construction and regulation of multi-agent systems.
Intelligent Techniques for Planning by Ioannis Vlahavas,Dimitris Vrakas Pdf
The Intelligent Techniques for Planning presents a number of modern approaches to the area of automated planning. These approaches combine methods from classical planning such as the construction of graphs and the use of domain-independent heuristics with techniques from other areas of artificial intelligence. This book discuses, in detail, a number of state-of-the-art planning systems that utilize constraint satisfaction techniques in order to deal with time and resources, machine learning in order to utilize experience drawn from past runs, methods from knowledge systems for more expressive representation of knowledge and ideas from other areas such as Intelligent Agents. Apart from the thorough analysis and implementation details, each chapter of the book also provides extensive background information about its subject and presents and comments on similar approaches done in the past.
Methods and Applications of Artificial Intelligence by Ioannis P. Vlahavas,Constantine D. Spyropoulos Pdf
This book constitutes the refereed proceedings of the Second Hellenic Conference on Artificial Intelligence, SETN 2002, held in Thessaloniki, Greece, in April 2002. The 42 revised full papers presented together with two invited contributions were carefully reviewed and selected for inclusion in the book. The papers are organized in topical sections on knowledge representation and reasoning, logic programming and constraint satisfaction, planning and scheduling, natural language processing, human-computer interaction, machine learning, intelligent Internet and multiagent systems, and intelligent applications.
Innovations in Multi-Agent Systems and Application – 1 by Dipti Srinivasan Pdf
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.
Programming Multi-Agent Systems by Rafael H. Bordini,Mehdi Dastani,Amal El Fallah Seghrouchni Pdf
This book constitutes the thoroughly refereed post-proceedings of the Third International Workshop on Programming Multi-Agent Systems, ProMAS 2005, held in Utrecht, The Netherlands in July 2005 as an associated event of AAMAS 2005, the main international conference on autonomous agents and multi-agent systems. The 14 revised full papers presented together with 2 invited articles are organized in topical sections on multi-agent techniques and issues, multi-agent programming, and multi-agent platforms and organization.
Multi-agent system (MAS) is an expanding field in science and engineering. It merges classical fields like game theory with modern ones like machine learning and computer science. This book provides a succinct introduction to the subject, covering the theoretical fundamentals as well as the latter developments in a coherent and clear manner. The book is centred on practical applications rather than introductory topics. Although it occasionally makes reference to the concepts involved, it will do so primarily to clarify real-world applications. The inner chapters cover a wide spectrum of issues related to MAS uses, which include collision avoidance, automotive applications, evacuation simulation, emergence analyses, cooperative control, context awareness, data (image) mining, resilience enhancement and the management of a single-user multi-robot.
An Application Science for Multi-Agent Systems by Thomas A. Wagner Pdf
An Application Science For Multi-Agent Systems addresses the complexity of choosing which multi-agent control technologies are appropriate for a given problem domain or a given application. Without such knowledge, when faced with a new application domain, agent developers must rely on past experience and intuition to determine whether a multi-agent system is the right approach, and if so, how to structure the agents, how to decompose the problem, and how to coordinate the activities of the agents, and so forth. This unique collection of contributions, written by leading international researchers in the agent community, provides valuable insight into the issues of deciding which technique to apply and when it is appropriate to use them. The contributions also discuss potential trade-offs or caveats involved with each decision. An Application Science For Multi-Agent Systems is an excellent reference for anyone involved in developing multi-agent systems.
Autonomous Dynamic Reconfiguration in Multi-Agent Systems by Markus Hannebauer Pdf
High communication efforts and poor problem solving results due to restricted overview are two central issues in collaborative problem solving. This work addresses these issues by introducing the processes of agent melting and agent splitting that enable individual problem solving agents to continually and autonomously reconfigure and adapt themselves to the particular problem to be solved. The author provides a sound theoretical foundation of collaborative problem solving itself and introduces various new design concepts and techniques to improve its quality and efficiency, such as the multi-phase agreement finding protocol for external problem solving, the composable belief-desire-intention agent architecture, and the distribution-aware constraint specification architecture for internal problem solving. The practical relevance and applicability of the concepts and techniques provided are demonstrated by using medical appointment scheduling as a case study.
Advances in Artificial Intelligence by Grigoris Antoniou,George Potamias,Costas Spyropoulos,Dimitris Plexousakis Pdf
This book constitutes the refereed proceedings of the 4th Hellenic Conference on Artificial Intelligence, SETN 2006, held at Heraklion, Crete, Greece in May 2006. The 43 revised full papers and extended abstracts of 34 revised short papers presented together with 2 invited contributions address many areas of artificial intelligence; particular fields of interest include: logic programming, knowledge-based systems, intelligent information retrieval, machine learning, neural nets, genetic algorithms, and more.
This book is a collection of 29 excellent works and comprised of three sections: task oriented approach, bio inspired approach, and modeling/design. In the first section, applications on formation, localization/mapping, and planning are introduced. The second section is on behavior-based approach by means of artificial intelligence techniques. The last section includes research articles on development of architectures and control systems.
Nature-Inspired Computation and Swarm Intelligence by Xin-She Yang Pdf
Nature-inspired computation and swarm intelligence have become popular and effective tools for solving problems in optimization, computational intelligence, soft computing and data science. Recently, the literature in the field has expanded rapidly, with new algorithms and applications emerging. Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications is a timely reference giving a comprehensive review of relevant state-of-the-art developments in algorithms, theory and applications of nature-inspired algorithms and swarm intelligence. It reviews and documents the new developments, focusing on nature-inspired algorithms and their theoretical analysis, as well as providing a guide to their implementation. The book includes case studies of diverse real-world applications, balancing explanation of the theory with practical implementation. Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications is suitable for researchers and graduate students in computer science, engineering, data science, and management science, who want a comprehensive review of algorithms, theory and implementation within the fields of nature inspired computation and swarm intelligence. Introduces nature-inspired algorithms and their fundamentals, including: particle swarm optimization, bat algorithm, cuckoo search, firefly algorithm, flower pollination algorithm, differential evolution and genetic algorithms as well as multi-objective optimization algorithms and others Provides a theoretical foundation and analyses of algorithms, including: statistical theory and Markov chain theory on the convergence and stability of algorithms, dynamical system theory, benchmarking of optimization, no-free-lunch theorems, and a generalized mathematical framework Includes a diversity of case studies of real-world applications: feature selection, clustering and classification, tuning of restricted Boltzmann machines, travelling salesman problem, classification of white blood cells, music generation by artificial intelligence, swarm robots, neural networks, engineering designs and others
