McGraw-Hill Book Co., NY, 1983, 436 pgs, Diagrams & illus, Exercises, References, Index.
Condition: Very Good overall, gray hardcover, titles in silver on spine and front. The binding is sound and secure, pages clean and unmarked.
See all items by Elaine Rich
Item DescriptionWhat is Artificial Intelligence - A Definition, Underlying Assumption, What is an A.I. Technique, Level of the Model, Criteria for Success, Some General References, One Final Word;
PROBLEM SOLVING - Problems & Problem Spaces -- Defining the Problem as a State Space Search, Problem Characteristics, Production System Characteristics, Additional Problems; Basic Problem-Solving Methods -- Forward versus Backward Reasoning, Problem Trees versus Problem Graphs, Knowledge Representation & the Frame Problem, Matching, Heuristic Functions, Weak Methods, Analyzing Search Algorithms; Game Playing -- Overview, Minimax Search Procedure, Adding Alpha-Beta Cutoffs, Additional Refinements, Limitations of the Method;
KNOWLEDGE REPRESENTATION - Knowledge Representation Using Predicate Logic-- Intro to Representation, Representing Simple Facts in Logic, Augmenting the Representation with Computable Functions & Predicates, Resolution, Natural Deduction; Knowledge Representation Using Other Logics -- Nonmonotonic Reasoning, Statistical & Probabilistic Reasoning;Structural Representations of Knowledge -- Declarative Representations, Procedural Representation;
ADVANCED TOPICS - Advanced Problem-Solving Systems -- Planning, System Organization, Expert Systems; Natural Language Understanding-- Intro, Understanding Single Sentences, Understanding Multiple Sentences, Going the Other Way - Language Generation, Going Both Ways - Machine Translation; Perception - Why is Perception Hard, Techniques Used in Solving Perceptual Problems, Constraint Satisfaction - The Waltz Algorithm; Learning -- What is Learning, Random Learning & Neural Nets, Rote Learning, Learning by Parameter Adjustment, Learning by GPS, Concept Learning, Discovery as Learning -- AM, Learning by Analogy;
Implementing A.I. Systems- Languages & Machines -- A.I. Languages - The Important Characteristics, IPL, LISP, SAIL, PLANNER, KRL, PROLOG, Summary, Computer Architectures for A.I. Applications, Conclusion -- Components of An A.I. Program, more .