A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence

A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence
Author: Nikos Kolobov
Publisher: Springer Nature
Total Pages: 71
Release: 2022-06-01
Genre: Computers
ISBN: 3031015436

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.

A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence

A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence
Author: Nikos Kolobov
Publisher: Springer Nature
Total Pages: 71
Release: 2022-06-01
Genre: Computers
ISBN: 3031015436

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.

A Concise Introduction to Decentralized POMDPs

A Concise Introduction to Decentralized POMDPs
Author: Frans A. Oliehoek
Publisher: Springer
Total Pages: 146
Release: 2016-06-03
Genre: Computers
ISBN: 3319289292

This book introduces multiagent planning under uncertainty as formalized by decentralized partially observable Markov decision processes (Dec-POMDPs). The intended audience is researchers and graduate students working in the fields of artificial intelligence related to sequential decision making: reinforcement learning, decision-theoretic planning for single agents, classical multiagent planning, decentralized control, and operations research.

A Concise Introduction to Decentralized POMDPs

A Concise Introduction to Decentralized POMDPs
Author: Frans A. Oliehoek
Publisher: Springer
Total Pages: 146
Release: 2016-06-03
Genre: Computers
ISBN: 3319289292

This book introduces multiagent planning under uncertainty as formalized by decentralized partially observable Markov decision processes (Dec-POMDPs). The intended audience is researchers and graduate students working in the fields of artificial intelligence related to sequential decision making: reinforcement learning, decision-theoretic planning for single agents, classical multiagent planning, decentralized control, and operations research.

Multi-agent Systems

Multi-agent Systems
Author: Jacques Ferber
Publisher: Addison-Wesley Professional
Total Pages: 536
Release: 1999
Genre: Computers
ISBN:

In this book, Jacques Ferber has brought together all the recent developments in the field of multi-agent systems - an area that has seen increasing interest and major developments over the last few years. The author draws on work carried out in various disciplines, including information technology, sociology and cognitive psychology to provide a coherent and instructive picture of the current state-of-the-art. The book introduces and defines the fundamental concepts that need to be understood, clearly describes the work that has been done, and invites readers to reflect upon the possibilities of the future.

Population-Based Approaches to the Resource-Constrained and Discrete-Continuous Scheduling

Population-Based Approaches to the Resource-Constrained and Discrete-Continuous Scheduling
Author: Ewa Ratajczak-Ropel
Publisher: Springer
Total Pages: 247
Release: 2017-08-21
Genre: Technology & Engineering
ISBN: 3319628933

This book addresses two of the most difficult and computationally intractable classes of problems: discrete resource constrained scheduling, and discrete-continuous scheduling. The first part of the book discusses problems belonging to the first class, while the second part deals with problems belonging to the second class. Both parts together offer valuable insights into the possibility of implementing modern techniques and tools with a view to obtaining high-quality solutions to practical and, at the same time, computationally difficult problems. It offers a valuable source of information for practitioners dealing with the real-world scheduling problems in industry, management and administration. The authors have been working on the respective problems for the last decade, gaining scientific recognition through publications and active participation in the international scientific conferences, and their results are obtained using population-based methods. Dr E. Ratajczk-Ropel explores multiple agent and A-Team concepts, while Dr A. Skakovski focuses on evolutionary algorithms with a particular focus on the population learning paradigm.

Innovations in Multi-Agent Systems and Application – 1

Innovations in Multi-Agent Systems and Application – 1
Author: Dipti Srinivasan
Publisher: Springer Science & Business Media
Total Pages: 303
Release: 2010-08-10
Genre: Computers
ISBN: 3642144349

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.

PRICAI 2019: Trends in Artificial Intelligence

PRICAI 2019: Trends in Artificial Intelligence
Author: Abhaya C. Nayak
Publisher: Springer Nature
Total Pages: 789
Release: 2019-08-23
Genre: Computers
ISBN: 3030299082

This three-volume set, LNAI 11670, LNAI 11671, and LNAI 11672 constitutes the thoroughly refereed proceedings of the 16th Pacific Rim Conference on Artificial Intelligence, PRICAI 2019, held in Cuvu, Yanuca Island, Fiji, in August 2019. The 111 full papers and 13 short papers presented in these volumes were carefully reviewed and selected from 265 submissions. PRICAI covers a wide range of topics such as AI theories, technologies and their applications in the areas of social and economic importance for countries in the Pacific Rim.

Advances in Intelligent and Distributed Computing

Advances in Intelligent and Distributed Computing
Author: Costin Badica
Publisher: Springer
Total Pages: 315
Release: 2010-04-25
Genre: Computers
ISBN: 3540749306

This book presents the proceedings of the 1st International Symposium on Intelligent and Distributed Computing, IDC 2007, held in Craiova, Romania, October 2007. Coverage includes: autonomous and adaptive computing; data mining and knowledge discovery; distributed problem solving and decision making; e-business, e-health and e-learning; genetic algorithms; image processing; information retrieval; intelligence in mobile and ubiquitous computing.