Agent-Based Hybrid Intelligent Systems

Agent-Based Hybrid Intelligent Systems

Author: Zili Zhang (Ph.D.)

Publisher: Springer Science & Business Media

Published: 2004-01-28

Total Pages: 200

ISBN-13: 3540209085

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Solving complex problems in real-world contexts, such as financial investment planning or mining large data collections, involves many different sub-tasks, each of which requires different techniques. To deal with such problems, a great diversity of intelligent techniques are available, including traditional techniques like expert systems approaches and soft computing techniques like fuzzy logic, neural networks, or genetic algorithms. These techniques are complementary approaches to intelligent information processing rather than competing ones, and thus better results in problem solving are achieved when these techniques are combined in hybrid intelligent systems. Multi-Agent Systems are ideally suited to model the manifold interactions among the many different components of hybrid intelligent systems. This book introduces agent-based hybrid intelligent systems and presents a framework and methodology allowing for the development of such systems for real-world applications. The authors focus on applications in financial investment planning and data mining.


Engineering Intelligent Hybrid Multi-Agent Systems

Engineering Intelligent Hybrid Multi-Agent Systems

Author: Rajiv Khosla

Publisher: Springer Science & Business Media

Published: 1997-09-30

Total Pages: 438

ISBN-13: 9780792399827

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Engineering Intelligent Hybrid Multi-Agent Systems is about building intelligent hybrid systems. Included is coverage of applications and design concepts related to fusion systems, transformation systems and combination systems. These applications are in areas involving hybrid configurations of knowledge-based systems, case-based reasoning, fuzzy systems, artificial neural networks, genetic algorithms, and in knowledge discovery and data mining. Through examples and applications a synergy of these subjects is demonstrated. The authors introduce a multi-agent architectural theory for engineering intelligent associative hybrid systems. The architectural theory is described at both the task structure level and the computational level. This problem-solving architecture is relevant for developing knowledge agents and information agents. An enterprise-wide system modeling framework is outlined to facilitate forward and backward integration of systems developed in the knowledge, information, and data engineering layers of an organization. In the modeling process, software engineering aspects like agent oriented analysis, design and reuse are developed and described. Engineering Intelligent Hybrid Multi-Agent Systems is the first book in the field to provide details of a multi-agent architecture for building intelligent hybrid systems.


PRICAI 2002: Trends in Artificial Intelligence

PRICAI 2002: Trends in Artificial Intelligence

Author: Mitsuru Ishizuka

Publisher: Springer Science & Business Media

Published: 2002-08-07

Total Pages: 643

ISBN-13: 3540440380

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This book constitutes the refereed proceedings of the 7th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2002, held in Tokyo, Japan in August 2002. The 57 revised full papers presented together with 5 invited contributions and 26 posters were carefully reviewed and selected from 161 submissions. The papers are organized in topical sections on logic and AI foundations, representation and reasoning of actions, constraint satisfaction, foundations of agents, foundations of learning, reinforcement learning, knowledge acquisition and management, data mining and knowledge discovery, neural network learning, learning for robots, multi-agent applications, document analysis, Web intelligence, bioinformatics, intelligent learning environments, face recognition, and multimedia and emotion.


Transactions on Intelligent Welding Manufacturing

Transactions on Intelligent Welding Manufacturing

Author: Shanben Chen

Publisher: Springer Nature

Published: 2020-08-31

Total Pages: 138

ISBN-13: 9811569223

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The primary aim of this volume is to provide researchers and engineers from both academic and industry with up-to-date coverage of new results in the field of robotic welding, intelligent systems and automation. The book is mainly based on papers selected from the 2020 International Conference on Robotic Welding, Intelligence and Automation (RWIA’2020) in Shanghai and Lanzhou, China. The articles show that the intelligentized welding manufacturing (IWM) is becoming an inevitable trend with the intelligentized robotic welding as the key technology. The volume is divided into four logical parts: Intelligent Techniques for Robotic Welding, Sensing of Arc Welding Processing, Modeling and Intelligent Control of Welding Processing, as well as Intelligent Control and its Applications in Engineering.


Autonomous Intelligent Systems: Multi-Agents and Data Mining

Autonomous Intelligent Systems: Multi-Agents and Data Mining

Author: Vladimir Gorodetsky

Publisher: Springer

Published: 2007-07-23

Total Pages: 334

ISBN-13: 3540728392

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This book constitutes the refereed proceedings of the Second International Workshop on Autonomous Intelligent Systems: Agents and Data Mining, AIS-ADM 2007, held in St. Petersburg, Russia in June 2007. The 17 revised full papers and six revised short papers presented together with four invited lectures cover agent and data mining, agent competition and data mining, as well as text mining, semantic Web, and agents.


Active Media Technology

Active Media Technology

Author: Jian Ping Li

Publisher: World Scientific

Published: 2003-01-01

Total Pages: 544

ISBN-13: 9789812704313

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Seeking to capture the essence of the current state of research in active media technology, this volume identifies the changes and opportunities - both current and future - in the field. The papers are taken from the Second International Conference on Active Media Technology, held in China in 2003. Researchers such as Professor Ning Zhong from the Maebashi Institute of Technology, Professor John Yen from the Pennsylvania State University, and Professor Sanker K. Pal from the Indian Statistical Institute present their research papers.


Innovations in Multi-Agent Systems and Application – 1

Innovations in Multi-Agent Systems and Application – 1

Author: Dipti Srinivasan

Publisher: Springer Science & Business Media

Published: 2010-08-10

Total Pages: 303

ISBN-13: 3642144349

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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.


Agent-Based Hybrid Intelligent Systems: an Agent-Based Framework for Complex Problem Solving

Agent-Based Hybrid Intelligent Systems: an Agent-Based Framework for Complex Problem Solving

Author: Zili Zhang

Publisher:

Published: 2004

Total Pages: 196

ISBN-13: 9781280306785

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Solving complex problems in real-world contexts, such as financial investment planning or mining large data collections, involves many different sub-tasks, each of which requires different techniques. To deal with such problems, a great diversity of intelligent techniques are available, including traditional techniques like expert systems approaches and soft computing techniques like fuzzy logic, neural networks, or genetic algorithms. These techniques are complementary approaches to intelligent information processing rather than competing ones, and thus better results in problem solving are achieved when these techniques are combined in hybrid intelligent systems. Multi-Agent Systems are ideally suited to model the manifold interactions among the many different components of hybrid intelligent systems.This book introduces agent-based hybrid intelligent systems and presents a framework and methodology allowing for the development of such systems for real-world applications. The authors focus on applications in financial investment planning and data mining.


An Introduction to MultiAgent Systems

An Introduction to MultiAgent Systems

Author: Michael Wooldridge

Publisher: John Wiley & Sons

Published: 2009-06-22

Total Pages: 484

ISBN-13: 0470519460

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The study of multi-agent systems (MAS) focuses on systems in which many intelligent agents interact with each other. These agents are considered to be autonomous entities such as software programs or robots. Their interactions can either be cooperative (for example as in an ant colony) or selfish (as in a free market economy). This book assumes only basic knowledge of algorithms and discrete maths, both of which are taught as standard in the first or second year of computer science degree programmes. A basic knowledge of artificial intelligence would useful to help understand some of the issues, but is not essential. The book’s main aims are: To introduce the student to the concept of agents and multi-agent systems, and the main applications for which they are appropriate To introduce the main issues surrounding the design of intelligent agents To introduce the main issues surrounding the design of a multi-agent society To introduce a number of typical applications for agent technology After reading the book the student should understand: The notion of an agent, how agents are distinct from other software paradigms (e.g. objects) and the characteristics of applications that lend themselves to agent-oriented software The key issues associated with constructing agents capable of intelligent autonomous action and the main approaches taken to developing such agents The key issues in designing societies of agents that can effectively cooperate in order to solve problems, including an understanding of the key types of multi-agent interactions possible in such systems The main application areas of agent-based systems