Lecture Notes in Artificial Intelligence 1st edition by Lawrence Cavedon, Anand Rao, Wayne Wobcke ISBN 3540626867  978-3540626862

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ISBN 10: 3540626867
ISBN 13: ‎ 978-3540626862
Author: Lawrence Cavedon, Anand Rao, Wayne Wobcke

The agents approach is not just another abstract computing paradigm, but has matured during recent years into a booming research area and software engineering technology which holds great promise for the design and application of complex distributed systems.
This book presents 12 revised full chapters grouped around 3 main topics in intelligent agent systems; agent architectures, formal theories of rationality and cooperation and collaboration. Among the topics addressed are software agents, BDI architectures, social commitment, believable agents and artificial life. The book is based on the Workshop on Theoretical and Practical Foundations of Intelligent Agents held at the Fourth Pacific Rim International Conference on Artificial Intelligence in Cairns, Australia, in August 1996.

Lecture Notes in Artificial Intelligence 1st Table of contents:

Preface

• Introduction to the Lecture Notes Series
• Acknowledgments

Chapter 1: Artificial Intelligence: An Overview

• Defining Artificial Intelligence
• History and Evolution of AI
• AI’s Role in Modern Technology
• Scope and Challenges in AI

Chapter 2: Problem Solving and Search Algorithms

• Classical Search Algorithms: DFS, BFS
• A* and Heuristic Search
• Optimization and Constraints
• Advanced Search Techniques
• Applications of Search in AI

Chapter 3: Knowledge Representation

• Overview of Knowledge Representation
• Symbolic vs. Sub-symbolic Representation
• Logic and Inference Systems
• Semantic Networks, Frames, and Ontologies
• Applications in AI Systems

Chapter 4: Machine Learning

• Overview of Machine Learning Techniques
• Supervised Learning: Decision Trees, SVM, Neural Networks
• Unsupervised Learning: Clustering, Dimensionality Reduction
• Reinforcement Learning
• Applications and Challenges of Machine Learning

Chapter 5: Natural Language Processing (NLP)

• Introduction to NLP
• Syntax and Semantics in NLP
• Text Mining and Language Models
• Machine Translation
• Applications of NLP

Chapter 6: Robotics and Autonomous Systems

• Fundamentals of Robotics
• Robot Perception and Action
• Motion Planning and Control
• Autonomous Vehicles
• Challenges in Robotic Systems

Chapter 7: Expert Systems

• Structure of Expert Systems
• Knowledge Base and Inference Engine
• Rule-Based and Fuzzy Logic Systems
• Applications in Decision Support
• Case Studies of Expert Systems in Industry

Chapter 8: Artificial Intelligence in Practice

• AI Applications in Healthcare, Finance, and Manufacturing
• AI for Social Good: Education, Environment, and Governance
• AI for Personal Assistants and Customer Support
• Ethical Implications of AI Applications

Chapter 9: The Future of Artificial Intelligence

• Emerging Trends and New Frontiers in AI
• AI and the Internet of Things (IoT)
• AI and Quantum Computing
• Ethical, Legal, and Societal Impacts
• AI in the Coming Decades

Index

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