6 Best Books on Agent Based Intelligent Systems

“Agent-Based Hybrid Intelligent Systems: An Agent-Based Framework for Complex Problem Solving (Lecture Notes in Computer Science)” Book Review: This book is designed for postgraduate students of Computer Science Engineering and can also be beneficial to professionals working in the field of artificial intelligence. It addresses complex real-life problems, including mining large amounts of data and financial investment planning. The book covers both expert system and soft computing techniques, and provides a detailed discussion on multi-agent systems in hybrid intelligent systems. Topics such as fuzzy logic, genetic algorithms, and neural networks are also covered. The book follows a methodology-based approach, including real-world case studies and numerical analysis in the field of data mining.

“Intelligent Agents: Specification, Modeling, and Application” Book Review: This book is primarily designed for postgraduate students in Computer Science Engineering and can serve as a reference for PhD scholars. It discusses the potential of intelligent agents and examines the transformation of the web from a passive medium to a highly interactive one. The book features papers presented at the 4th Pacific Rim International Workshop on multi-agents and covers autonomous and multi-agent systems in great detail. It also offers numerous practical scenarios and includes carefully curated, highly-researched material on the topic of intelligent agents. The book is comprised of select papers from PRIMA 2001.

“Intelligent Agents: ECAI-94 Workshop on Agent Theories, Architectures, and Languages, Amsterdam, The Netherlands” Book Review: This book is targeted towards researchers, PhD scholars, and professionals seeking knowledge of advanced intelligent agent technologies. It comprises 24 research papers that were accepted for the Agent Theories workshop at ECAI-94. In addition to covering topics related to computer architectures and languages, the book provides both theoretical and practical approaches to designing language and architecture. The volume editors conducted comprehensive surveys that highlight the key issues in intelligent agents. This book provides detailed numerical derivations necessary to prove the theories and addresses various practical implementation issues of software agents.

“Building Intelligent Agents: An Apprenticeship, Multistrategy Learning Theory, Methodology, Tool and Case Studies” Book Review: This book is designed for postgraduate students in Computer Science engineering and can serve as a reference for research scholars. It provides an approach to building intelligent agents, including theory, methodology, and tools. The book covers the development of various agents, such as educational assessment agents, support agents, and engineering design agents. It also includes the creation of a virtual military commander and a human apprentice. The book demonstrates how agents can learn from their teachers using a variety of machine learning and knowledge acquisition techniques. This book takes a practical approach, presenting detailed case studies on building different types of agents. It also provides mathematical and conceptual derivations of many machine learning algorithms.

“Intelligent Agents in Data-intensive Computing (Studies in Big Data)” Book Review: This book targets students and professionals researching in the Big Data field. It discusses new methods for exploring agent-based models, as well as simulations and implementations for data-intensive applications. The book provides a review of cross-disciplinary approaches in cloud environments, as well as a comprehensive discussion of issues in distributed computational environments. Real-life practical scenarios are covered, and some of the mentioned formulas are accompanied by mathematical derivations.

“Building Intelligent .NET Applications: Agents, Data Mining, Rule-Based Systems, and Speech Processing (Addison-Wesley Microsoft Technology)” Book Review: The target audience of this book is undergraduate students of computer science engineering, although postgraduate students can also benefit from it in creating intelligent applications. It covers fundamental artificial intelligence (AI) techniques for solving software problems and emphasizes creating intelligent applications using the .NET framework. The book delves into data mining, speech recognition, intelligent agents, and rule-based systems. It presents accessible and usable AI technologies, including several sample real-world applications, with a practical approach that teaches specific techniques in detail.