Fundamentals of artificial intelligence / K. R. Chowdhary.

Includes bibliographical references and index.

Intro -- Preface -- Acknowledgements -- Contents -- About the Author -- Acronyms -- 1 Introducing Artificial Intelligence -- 1.1 Introduction -- 1.2 The Turing Test -- 1.3 Goals of AI -- 1.4 Roots of AI -- 1.4.1 Philosophy -- 1.4.2 Logic and Mathematics -- 1.4.3 Computation -- 1.4.4 Psychology and Cognitive Science -- 1.4.5 Biology and Neuroscience -- 1.4.6 Evolution -- 1.5 Artificial Consciousness -- 1.6 Techniques Used in AI -- 1.7 Sub-fields of AI -- 1.7.1 Speech Processing -- 1.7.2 Natural Language Processing -- 1.7.3 Planning -- 1.7.4 Engineering and Expert Systems -- 1.7.5 Fuzzy Systems
1.7.6 Models of Brain and Evolution -- 1.8 Perception, Understanding, and Action -- 1.9 Physical Symbol System Hypothesis -- 1.9.1 Formal System -- 1.9.2 Symbols and Physical Symbol Systems -- 1.9.3 Formal Logic -- 1.9.4 The Stored Program Concept -- 1.10 Considerations for Knowledge Representation -- 1.10.1 Defining the Knowledge -- 1.10.2 Objective of Knowledge Representation -- 1.10.3 Requirements of a Knowledge Representation -- 1.10.4 Practical Aspects of Representations -- 1.10.5 Components of a Representation -- 1.11 Knowledge Representation Using Natural Language -- 1.12 Summary
2.8.2 Axiomatics and Formalism -- 2.9 Summary -- References -- 3 First Order Predicate Logic -- 3.1 Introduction -- 3.2 Representation in Predicate Logic -- 3.3 Syntax and Semantics -- 3.4 Conversion to Clausal Form -- 3.5 Substitutions and Unification -- 3.5.1 Composition of Substitutions -- 3.5.2 Unification -- 3.6 Resolution Principle -- 3.6.1 Theorem Proving Formalism -- 3.6.2 Proof by Resolution -- 3.7 Complexity of Resolution Proof -- 3.8 Interpretation and Inferences -- 3.8.1 Herbrand's Universe -- 3.8.2 Herbrand's Theorem -- 3.8.3 The Procedural Interpretation -- 3.9 Most General Unifiers
3.9.1 Lifting -- 3.9.2 Unification Algorithm -- 3.10 Unfounded Sets -- 3.11 Summary -- References -- 4 Rule Based Reasoning -- 4.1 Introduction -- 4.2 An Overview of RBS -- 4.3 Forward Chaining -- 4.3.1 Forward Chaining Algorithm -- 4.3.2 Conflict Resolution -- 4.3.3 Efficiency in Rule Selection -- 4.3.4 Complexity of Preconditions -- 4.4 Backward Chaining -- 4.4.1 Backward Chaining Algorithm -- 4.4.2 Goal Determination -- 4.5 Forward Versus Backward Chaining -- 4.6 Typical RB System -- 4.7 Other Systems of Reasoning -- 4.7.1 Model-Based Systems -- 4.7.2 Case-Based Reasoning -- 4.8 Summary.

Fundamentals of Artificial Intelligence introduces the foundations of present day AI and provides coverage to recent developments in AI such as Constraint Satisfaction Problems, Adversarial Search and Game Theory, Statistical Learning Theory, Automated Planning, Intelligent Agents, Information Retrieval, Natural Language & Speech Processing, and Machine Vision. The book features a wealth of examples and illustrations, and practical approaches along with the theoretical concepts. It covers all major areas of AI in the domain of recent developments. The book is intended primarily for students who major in computer science at undergraduate and graduate level but will also be of interest as a foundation to researchers in the area of AI.