Multiagent Systems and Applications
Multiagent Systems and Applications

Author: Maria Ganzha

Publisher: Springer Science & Business Media

Published: 2012-10-06

Total Pages: 296

ISBN-13: 3642333230

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The focus of the book is on completed implementations of agent-based software systems. Here, agent technology is considered broadly, starting from development of agent platforms, all the way through systems actually implemented. The covered topics also include lessons learned during implementation of agent platforms and the reflection on the process of development and application of agent-based systems. The book includes 10 chapters where interested reader can find discussion of important issues encountered during development of well-known agent platforms such as JADE and Jadex as well as some interesting experiences in developing a new platform that combines software agent and Web Services. Furthermore, the book shows readers several valuable examples of applications based on multi-agent systems including simulations, agents in autonomous negotiations and agents in public administration modelling. We believe that the book will prove useful to the researchers, professors and the practitioners in all disciplines including science and technology.

Multi-Objective Decision Making
Multi-Objective Decision Making

Author: Diederik M. Roijers

Publisher: Morgan & Claypool Publishers

Published: 2017-04-20

Total Pages: 174

ISBN-13: 1681731827

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Many real-world decision problems have multiple objectives. For example, when choosing a medical treatment plan, we want to maximize the efficacy of the treatment, but also minimize the side effects. These objectives typically conflict, e.g., we can often increase the efficacy of the treatment, but at the cost of more severe side effects. In this book, we outline how to deal with multiple objectives in decision-theoretic planning and reinforcement learning algorithms. To illustrate this, we employ the popular problem classes of multi-objective Markov decision processes (MOMDPs) and multi-objective coordination graphs (MO-CoGs). First, we discuss different use cases for multi-objective decision making, and why they often necessitate explicitly multi-objective algorithms. We advocate a utility-based approach to multi-objective decision making, i.e., that what constitutes an optimal solution to a multi-objective decision problem should be derived from the available information about user utility. We show how different assumptions about user utility and what types of policies are allowed lead to different solution concepts, which we outline in a taxonomy of multi-objective decision problems. Second, we show how to create new methods for multi-objective decision making using existing single-objective methods as a basis. Focusing on planning, we describe two ways to creating multi-objective algorithms: in the inner loop approach, the inner workings of a single-objective method are adapted to work with multi-objective solution concepts; in the outer loop approach, a wrapper is created around a single-objective method that solves the multi-objective problem as a series of single-objective problems. After discussing the creation of such methods for the planning setting, we discuss how these approaches apply to the learning setting. Next, we discuss three promising application domains for multi-objective decision making algorithms: energy, health, and infrastructure and transportation. Finally, we conclude by outlining important open problems and promising future directions.

Multi-Agent Energy Systems Simulation
Multi-Agent Energy Systems Simulation

Author: Tiago Pinto

Publisher:

Published: 2020

Total Pages: 190

ISBN-13: 9783039436507

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The synergy between artificial intelligence and power and energy systems is providing promising solutions to deal with the increasing complexity of the energy sector. Multi-agent systems, in particular, are widely used to simulate complex problems in the power and energy domain as they enable modeling dynamic environments and studying the interactions between the involved players. Multi-agent systems are suitable for dealing not only with problems related to the upper levels of the system, such as the transmission grid and wholesale electricity markets, but also to address challenges associated with the management of distributed generation, renewables, large-scale integration of electric vehicles, and consumption flexibility. Agent-based approaches are also being increasingly used for control and to combine simulation and emulation by enabling modeling of the details of buildings' electrical devices, microgrids, and smart grid components. This book discusses and highlights the latest advances and trends in multi-agent energy systems simulation. The addressed application topics include the design, modeling, and simulation of electricity markets operation, the management and scheduling of energy resources, the definition of dynamic energy tariffs for consumption and electrical vehicles charging, the large-scale integration of variable renewable energy sources, and mitigation of the associated power network issues.

Multi-Agent Systems and Applications
Multi-Agent Systems and Applications

Author: Michael Luck

Publisher: Springer Science & Business Media

Published: 2001-06-20

Total Pages: 1366

ISBN-13: 9783540423126

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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.

Artificial Superintelligence
Artificial Superintelligence

Author: Roman V. Yampolskiy

Publisher: MDPI

Published: 2020-04-30

Total Pages: 206

ISBN-13: 3039218549

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Attention in the AI safety community has increasingly started to include strategic considerations of coordination between relevant actors in the field of AI and AI safety, in addition to the steadily growing work on the technical considerations of building safe AI systems. This shift has several reasons: Multiplier effects, pragmatism, and urgency. Given the benefits of coordination between those working towards safe superintelligence, this book surveys promising research in this emerging field regarding AI safety. On a meta-level, the hope is that this book can serve as a map to inform those working in the field of AI coordination about other promising efforts. While this book focuses on AI safety coordination, coordination is important to most other known existential risks (e.g., biotechnology risks), and future, human-made existential risks. Thus, while most coordination strategies in this book are specific to superintelligence, we hope that some insights yield “collateral benefits” for the reduction of other existential risks, by creating an overall civilizational framework that increases robustness, resiliency, and antifragility.

Multi-Agent System Engineering
Multi-Agent System Engineering

Author: Francisco J. Garijo

Publisher: Springer

Published: 2007-07-23

Total Pages: 245

ISBN-13: 354048437X

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In the ten years since the first MAAMAW was held in 1989, at King's College, Cambridge, the field of Multi-Agent Systems (MAS) has flourished. It has attracted an increasing amount of theoretical and applied research. During this decade, important efforts have been made to establish the scientific and technical foundations of MAS. MAAMAW publications are testimony to the progress achieved in key areas such as agent modelling and reasoning, multi-agent interaction and communication, and multi-agent organisation and social structure. Research results have covered a wide range of inter-related topics in each area including agent architectures, reasoning models, logics, conflict resolution, negotiation, resource allocation, load balancing, learning; social behaviour and interaction, languages and protocols, interagent and agent-human communication, social models, agent roles, norms and social laws, and static and dynamic organisational structures. The feasibility and the viability of the proposed models and techniques have been demonstrated through MAS applications in heterogeneous domains including electronic commerce, co-operative work, telecommunications, social and biological systems, robotics, office and business automation, public administration, social simulations and banking. As the applicability of the technology became understood, the multi-agent paradigm has been progressively accepted by product managers and system developers, giving rise to a considerable amount of business expectation from industry. These expectations do not rest on the concept or metaphor of agent, but on the development of MAS useful in an industrial setting, with real-time systems presenting the biggest challenge.

Self-Aware Computing Systems
Self-Aware Computing Systems

Author: Samuel Kounev

Publisher: Springer

Published: 2017-01-30

Total Pages: 0

ISBN-13: 9783319474724

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This book provides formal and informal definitions and taxonomies for self-aware computing systems, and explains how self-aware computing relates to many existing subfields of computer science, especially software engineering. It describes architectures and algorithms for self-aware systems as well as the benefits and pitfalls of self-awareness, and reviews much of the latest relevant research across a wide array of disciplines, including open research challenges. The chapters of this book are organized into five parts: Introduction, System Architectures, Methods and Algorithms, Applications and Case Studies, and Outlook. Part I offers an introduction that defines self-aware computing systems from multiple perspectives, and establishes a formal definition, a taxonomy and a set of reference scenarios that help to unify the remaining chapters. Next, Part II explores architectures for self-aware computing systems, such as generic concepts and notations that allow a wide range of self-aware system architectures to be described and compared with both isolated and interacting systems. It also reviews the current state of reference architectures, architectural frameworks, and languages for self-aware systems. Part III focuses on methods and algorithms for self-aware computing systems by addressing issues pertaining to system design, like modeling, synthesis and verification. It also examines topics such as adaptation, benchmarks and metrics. Part IV then presents applications and case studies in various domains including cloud computing, data centers, cyber-physical systems, and the degree to which self-aware computing approaches have been adopted within those domains. Lastly, Part V surveys open challenges and future research directions for self-aware computing systems. It can be used as a handbook for professionals and researchers working in areas related to self-aware computing, and can also serve as an advanced textbook for lecturers and postgraduate students studying subjects like advanced software engineering, autonomic computing, self-adaptive systems, and data-center resource management. Each chapter is largely self-contained, and offers plenty of references for anyone wishing to pursue the topic more deeply.

Advances In Intelligent Control
Advances In Intelligent Control

Author: C J Harris

Publisher: CRC Press

Published: 1994-03-11

Total Pages: 384

ISBN-13: 9780748400669

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"Advances in intelligent Control" is a collection of essays covering the latest research in the field. Based on a special issue of "The International Journal of Control", the book is arranged in two parts. Part one contains recent contributions of artificial neural networks to modelling and control. Part two concerns itself primarily with aspects of fuzzy logic in intelligent control, guidance and estimation, although some of the contributions either make direct equivalence relationships to neural networks or use hybrid methods where a neural network is used to develop the fuzzy rule base.

Multi-Agent Systems
Multi-Agent Systems

Author: Adelinde M. Uhrmacher

Publisher: CRC Press

Published: 2018-10-08

Total Pages: 632

ISBN-13: 1351834673

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Methodological Guidelines for Modeling and Developing MAS-Based Simulations The intersection of agents, modeling, simulation, and application domains has been the subject of active research for over two decades. Although agents and simulation have been used effectively in a variety of application domains, much of the supporting research remains scattered in the literature, too often leaving scientists to develop multi-agent system (MAS) models and simulations from scratch. Multi-Agent Systems: Simulation and Applications provides an overdue review of the wide ranging facets of MAS simulation, including methodological and application-oriented guidelines. This comprehensive resource reviews two decades of research in the intersection of MAS, simulation, and different application domains. It provides scientists and developers with disciplined engineering approaches to modeling and developing MAS-based simulations. After providing an overview of the field’s history and its basic principles, as well as cataloging the various simulation engines for MAS, the book devotes three sections to current and emerging approaches and applications. Simulation for MAS — explains simulation support for agent decision making, the use of simulation for the design of self-organizing systems, the role of software architecture in simulating MAS, and the use of simulation for studying learning and stigmergic interaction. MAS for Simulation — discusses an agent-based framework for symbiotic simulation, the use of country databases and expert systems for agent-based modeling of social systems, crowd-behavior modeling, agent-based modeling and simulation of adult stem cells, and agents for traffic simulation. Tools — presents a number of representative platforms and tools for MAS and simulation, including Jason, James II, SeSAm, and RoboCup Rescue. Complete with over 200 figures and formulas, this reference book provides the necessary overview of experiences with MAS simulation and the tools needed to exploit simulation in MAS for future research in a vast array of applications including home security, computational systems biology, and traffic management.