Distributed Artificial Intelligence Meets Machine Learning Learning in Multi-Agent Environments

Distributed Artificial Intelligence Meets Machine Learning Learning in Multi-Agent Environments PDF Author: Gerhard Weiß
Publisher: Lecture Notes in Artificial Intelligence
ISBN:
Category : Computers
Languages : en
Pages : 314

Get Book Here

Book Description
This state-of-the-art report documents current and ongoing developments in the area of learning in DAI systems. It is indispensable reading for anybody active in the area and will serve as a valuable source of information and inspiration for AI and ML professionals wishing to learn about this new interdisciplinary field or to prepare themselves for doing relevant research.

Distributed Artificial Intelligence Meets Machine Learning Learning in Multi-Agent Environments

Distributed Artificial Intelligence Meets Machine Learning Learning in Multi-Agent Environments PDF Author: Gerhard Weiß
Publisher: Lecture Notes in Artificial Intelligence
ISBN:
Category : Computers
Languages : en
Pages : 314

Get Book Here

Book Description
This state-of-the-art report documents current and ongoing developments in the area of learning in DAI systems. It is indispensable reading for anybody active in the area and will serve as a valuable source of information and inspiration for AI and ML professionals wishing to learn about this new interdisciplinary field or to prepare themselves for doing relevant research.

A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence

A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence PDF Author: Nikos Kolobov
Publisher: Springer Nature
ISBN: 3031015436
Category : Computers
Languages : en
Pages : 71

Get Book Here

Book Description
Multiagent systems is an expanding field that blends classical fields like game theory and decentralized control with modern fields like computer science and machine learning. This monograph provides a concise introduction to the subject, covering the theoretical foundations as well as more recent developments in a coherent and readable manner. The text is centered on the concept of an agent as decision maker. Chapter 1 is a short introduction to the field of multiagent systems. Chapter 2 covers the basic theory of singleagent decision making under uncertainty. Chapter 3 is a brief introduction to game theory, explaining classical concepts like Nash equilibrium. Chapter 4 deals with the fundamental problem of coordinating a team of collaborative agents. Chapter 5 studies the problem of multiagent reasoning and decision making under partial observability. Chapter 6 focuses on the design of protocols that are stable against manipulations by self-interested agents. Chapter 7 provides a short introduction to the rapidly expanding field of multiagent reinforcement learning. The material can be used for teaching a half-semester course on multiagent systems covering, roughly, one chapter per lecture.

Distributed Artificial Intelligence, Agent Technology, and Collaborative Applications

Distributed Artificial Intelligence, Agent Technology, and Collaborative Applications PDF Author: Sugumaran, Vijayan
Publisher: IGI Global
ISBN: 1605661457
Category : Computers
Languages : en
Pages : 449

Get Book Here

Book Description
"This book is a catalyst for emerging research in intelligent information, specifically artificial intelligent technologies and applications to assist in improving productivity in many roles such as assistants to human operators and autonomous decision-making components of complex systems"--Provided by publisher.

Multi-Agent Systems and Agent-Based Simulation

Multi-Agent Systems and Agent-Based Simulation PDF Author: Jaime S. Sichman
Publisher: Springer
ISBN: 3540492461
Category : Computers
Languages : en
Pages : 245

Get Book Here

Book Description
Fifteen papers were presented at the first workshop on Multi-Agent Systems and Agent-Based Simulation held as part of the Agents World conference in Paris, July 4-- 6, 1998. The workshop was designed to bring together two developing communities: the multi-agent systems researchers who were the core participants at Agents World, and social scientists interested in using MAS as a research tool. Most of the social sciences were represented, with contributions touching on sociology, management science, economics, psychology, environmental science, ecology, and linguistics. The workshop was organised in association with SimSoc, an informal group of social scientists who have arranged an irregular series of influential workshops on using simulation in the social sciences beginning in 1992. While the papers were quite heterogeneous in substantive domain and in their disciplinary origins, there were several themes which recurred during the workshop. One of these was considered in more depth in a round table discussion led by Jim Doran at the end of the workshop on 'Representing cognition for social simulation', which addressed the issue of whether and how cognition should be modelled. Quite divergent views were expressed, with some participants denying that individual cognition needed to be modelled at all, and others arguing that cognition must be at the centre of social simulation.

The Handbook on Reasoning-Based Intelligent Systems

The Handbook on Reasoning-Based Intelligent Systems PDF Author: Kazumi Nakamatsu
Publisher: World Scientific
ISBN: 9814329487
Category : Computers
Languages : en
Pages : 680

Get Book Here

Book Description
This book consists of various contributions in conjunction with the keywords OC reasoningOCO and OC intelligent systemsOCO, which widely covers theoretical to practical aspects of intelligent systems. Therefore, it is suitable for researchers or graduate students who want to study intelligent systems generally."

Distributed Autonomous Robotic Systems 3

Distributed Autonomous Robotic Systems 3 PDF Author: Tim Lueth
Publisher: Springer Science & Business Media
ISBN: 3642721982
Category : Technology & Engineering
Languages : en
Pages : 417

Get Book Here

Book Description
Distributed autonomous robotic systems (DARS) are systems composed of multiple autonomous units such as modules, cells, processors, agents, and robots. Combination or cooperative operation of multiple autonomous units is expected to lead to desirable features such as flexibility, fault tolerance, and efficiency. The DARS is the leading established conference on distributed autonomous systems. All papers have the common goal to contribute solutions to the very demanding task of designing distributed systems to realize robust and intelligent robotic systems.

Multiagent Systems

Multiagent Systems PDF Author: Gerhard Weiss
Publisher: MIT Press
ISBN: 9780262731317
Category : Computers
Languages : en
Pages : 652

Get Book Here

Book Description
An introduction to multiagent systems and contemporary distributed artificial intelligence, this text provides coverage of basic topics as well as closely-related ones. It emphasizes aspects of both theory and application and includes exercises of varying degrees of difficulty.

Multi-Agent Systems for Concurrent Intelligent Design and Manufacturing

Multi-Agent Systems for Concurrent Intelligent Design and Manufacturing PDF Author: Weiming Shen
Publisher: CRC Press
ISBN: 1482289253
Category : Technology & Engineering
Languages : en
Pages : 403

Get Book Here

Book Description
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

Multi-Agent-Based Simulation II

Multi-Agent-Based Simulation II PDF Author: Jaime S. Sichman
Publisher: Springer Science & Business Media
ISBN: 3540006079
Category : Computers
Languages : en
Pages : 204

Get Book Here

Book Description
This volume presents extended and revised versions of the papers presented at the Third International Workshop on Multi-Agent Based Simulation (MABS 2002), a workshop federated with the First International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2002), which was held in Bologna, Italy, in July, 2002. This workshop was the third in the MABS series. The earlier two were - ganized as workshops of the two most recent ICMAS conferences (ICMAS 1998, Paris, France and ICMAS 2000, Boston, USA). Revised versions of the papers presented at these workshops were published as volumes 1534 and 1979 in the Lecture Notes in Arti?cial Intelligence series. One aim of the workshop was to develop stronger links between those wo- ing in the social sciences and those involved with multi-agent systems. We are pleased to note that many important conferences in various disciplines such as geography, economics, ecology, sociology, and physics have hosted workshops on MABS-related topics and that many respected journals publish papers that - clude elements of MABS. But although MABS is gradually acquiring legitimacy in many disciplinary ?elds, much remains to be done to clarify the potential use of MABS in these disciplines. Researchers from these disciplines have di?erent points of view on issues such as time-frame, space, geographical scales, or- nizational levels, etc. Moreover, the interest in MABS goes beyond the scienti?c community, as MABS models have been developed and used interactively with other communities as well.

Machine Learning: ECML 2001

Machine Learning: ECML 2001 PDF Author: Luc de Raedt
Publisher: Springer
ISBN: 3540447954
Category : Computers
Languages : en
Pages : 635

Get Book Here

Book Description
This book constitutes the refereed proceedings of the 12th European Conference on Machine Learning, ECML 2001, held in Freiburg, Germany, in September 2001. The 50 revised full papers presented together with four invited contributions were carefully reviewed and selected from a total of 140 submissions. Among the topics covered are classifier systems, naive-Bayes classification, rule learning, decision tree-based classification, Web mining, equation discovery, inductive logic programming, text categorization, agent learning, backpropagation, reinforcement learning, sequence prediction, sequential decisions, classification learning, sampling, and semi-supervised learning.