AI Algorithms Data Structures and Idioms in Prolog Lisp and Java 6th Edition by George Luger, William Stubblefield 0136070477 9780136070474

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Product details:

ISBN 10: 0136070477

ISBN 13: 9780136070474 

Author: George F. Luger; William A. Stubblefield

This book illustrates how to program AI algorithms in Lisp, Prolog, and Java. The book basically cover each topic 3 times in each language. Topics include: simple production-like system based on logic, logic-based learning, and natural language parsing.

In an inference engine based on first order logic, management of substitutions can get rather complicated, which is often glossed over in AI textbooks. But this book covers this aspect, as do “Paradigms of AI Programming”, “Structure and Interpretation of Computer Programs”, and Winston’s book on Common Lisp

Table of content:

Part I Language Idioms and the Master Programmer

Chapter 1 Idioms, Patterns, and Programming

Part II Programming in Prolog
Chapter 2 Prolog: Representation
Chapter 3 Abstract Data Types and Search
Chapter 4 Depth- Breadth-, and Best-First Search
Chapter 5 Meta-Linguistic Abstraction, Types, and Meta-Interpreters
Chapter 6 Three Meta-Interpreters: Prolog in Prolog, EXSHELL, and a Planner

Chapter 7 Machine Learning Algorithms in Prolog

Chapter 8 Natural Language Processing in Prolog 

Chapter 9 Dynamic Programming and the Earley Parser

Chapter 10 Prolog: Final Thoughts

Part III Programming in Lisp

Chapter 11S-Expressions, the Syntax of Lisp 
Chapter 12 Lists and Recursive Search
Chapter 13 Variables, Datratypes, and Search

Chapter 14 Higher-Order Functions and Flexible Search
Chapter 15 Unification and Embedded Languages in Lisp
Chapter 16 Logic programming in Lisp
Chapter 17 Lisp-shell: An Expert System Shell in Lisp
Chapter 18 Semantic Networks, Inheritance, and CLOS 
Chapter 19 Machine Learning in Lisp

Chapter 20 Lisp: Final Thoughts 267
Part IV Programming in Java
Chapter 21 Java, Representation and Object-Oriented Pro
Chapter 22 Problem Spaces and Search
Chapter 23 Java Representation for Predicate Calculus an
Chapter 24 A Logic-Based Reasoning SystemChapter 25 An Expert System Shell
Chapter 26 Case Studies: JESS and other Expert System Shells in Java зе
Chapter 27 ID3: Learning from Examples
Chapter 28 Genetic and Evolutionary Computing
Chapter 29 Case Studies: Java Machine Learning Software Available on the
Chapter 30 The Earley Parser: Dynamic Programming in Java
Chapter 31Case Studies: Java Natural Language Tools on the Web 
Chapter 32Conclusion: The Master Programmer

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