Artificial Intelligence Structures and Strategies for Complex Problem Solving

ISBN-10: 0321545893

ISBN-13: 9780321545893

Edition: 6th 2009

Authors: George F. Luger
List price: $193.40 Buy it from $51.02 Rent it from $21.69
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Description: KEY MESSAGE:In this accessible, comprehensive text, George Luger captures the essence of artificial intelligence-solving the complex problems that arise wherever computer technology is applied. Artificial Intelligence: Its Rootes and Scope:AI Early History and Applications.Artificial Intelligence as Representation and Search:The Predicate Calculus; Structures and Strategies for State Space Search; Heuristic Search; Stochastic Methods; Building Control Algorithms for State Space Search.Representation and Intelligence: The AI Challenge:Knowledge Representation; Strong Method Problem Solving; Reasoning in Uncertain Situations.Machine Learning:Machine Learning: Symbol-Based; Machine Learning: Connectionist; Machine Learning: Social and Emergent; Machine Learning: Probabilistically-Based.Advanced Topics for AI Problem Solving:Automated Reasoning; Understanding Natural Language.Epilogue:Artificial Intelligence as Empirical Enquiry.Languages and Programming Techniques for Artificial Intelligence:An Introduction to Prolog; An Introduction to Lisp; An Introduction to AI Algorithms in Java. For all readers interested in artificial intelligence.

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Book details

List price: $193.40
Edition: 6th
Copyright year: 2009
Publisher: Pearson Education
Publication date: 2/26/2008
Binding: Hardcover
Pages: 784
Size: 7.75" wide x 9.50" long x 1.25" tall
Weight: 3.190
Language: English

Artificial Intelligence: Its Roots and Scope
AI: History and Applications
From Eden to ENIAC: Attitudes toward Intelligence, Knowledge, and Human Artifice
Overview of AI Application Areas
Artificial Intelligence A Summary
Epilogue and References
Exercises
Artificial Intelligence as Representation and Search
The Predicate Calculus
Introduction
The Propositional Calculus
The Predicate Calculus
Using Inference Rules to Produce Predicate Calculus Expressions
Application: A Logic-Based Financial Advisor
Epilogue and References
Exercises
Structures and Strategies for State Space Search
Introduction
Graph Theory
Strategies for State Space Search
Using the State Space to Represent Reasoning with the Predicate Calculus
Epilogue and References
Exercises
Heuristic Search
Introduction
Hill Climbing and Dynamic Programming
The Best-First Search Algorithm
Admissibility, Monotonicity, and Informedness
Using Heuristics in Games
Complexity Issues
Epilogue and References
Exercises
stochastic methods
Introduction
The Elements of Counting
Elements of Probability Theory
Applications of the Stochastic Methodology
Bayes Theorem
Epilogue and References
Exercises
Control and Implementation of State Space Search
Introduction
Recursion-Based Search
Production Systems
The Blackboard Architecture for Problem Solving
Epilogue and References
Exercises
Capturing Intelligence: The AI Challenge
Knowledge Representation
Issues in Knowledge Representation
A Brief History of AI Representational Systems
Conceptual Graphs: A Network Language
Alternative Representations and Ontologies
Agent Based and Distributed Problem Solving
Epilogue and References
Exercises
Strong Method Problem Solving
Introduction
Overview of Expert System Technology
Rule-Based Expert Systems
Model-Based, Case Based, and Hybrid Systems
Planning
Epilogue and References
Exercises
Reasoning in Uncertain Situations
Introduction
Logic-Based Abductive Inference
Abduction: Alternatives to Logic
The Stochastic Approach to Uncertainty
Epilogue and References
Exercises
Machine Learning
Machine Learning: Symbol-Based
Introduction
A Framework for Symbol-based Learning
Version Space Search
The ID3 Decision Tree Induction Algorithm
Inductive Bias and Learnability
Knowledge and Learning
Unsupervised Learning
Reinforcement Learning
Epilogue and References
Exercises
Machine Learning: Connectionist
Introduction
Foundations for Connectionist Networks
Perceptron Learning
Backpropagation Learning
Competitive Learning
Hebbian Coincidence Learning
Attractor Networks or Memories
Epilogue and References
Exercises 506
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