Artificial Intelligence: Structures and Strategies for Complex Problem SolvingCombines the theoretical foundations of intelligent problem-solving with he data structures and algorithms needed for its implementation. The book presents logic, rule, object and agent-based architectures, along with example programs written in LISP and PROLOG. The practical applications of AI have been kept within the context of its broader goal: understanding the patterns of intelligence as it operates in this world of uncertainty, complexity and change. The introductory and concluding chapters take a new look at the potentials and challenges facing artificial intelligence and cognitive science.An extended treatment of knowledge-based problem-solving is given including model-based and case-based reasoning. Includes new material on:Fundamentals of search, inference and knowledge representatioAI algorithms and data structures in LISP and PROLOProduction systems, blackboards, and meta-interpreters including planers, rule-based reasoners, and inheritance systemsMachine-learning including ID3 with bagging and boosting, explanation based learning, PAC learning, and other forms of inductioNeural networks, including perceptrons, back propogation, Kohonen networks, Hopfield networks, Grossberg learning, and counterpropagationEmergent and social methods of learning and adaptation, including genetic algorithms, genetic programming and artificial lifeObject and agent-based problem solving and other forms of advanced knowledge representation |
Contents
PARTI | 1 |
REASONING WITH UNCERTAIN OR INCOMPLETE | 7 |
PART II | 33 |
Copyright | |
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Common terms and phrases
8-puzzle and/or graph applied approach arcs artificial intelligence assumptions backtrack behavior belief best-first search breadth-first search case-based case-based reasoning Chapter closed complexity conceptual graphs conclusion data-driven defined depth-first search described discussed element evaluation example expert systems formal function goal goal-driven search graph of Figure graph search heuristic search implement important inference rules interpretation iteration knight on square knight's tour knowledge base knowledge representation logical loop match memory minimax modus ponens move natural language nodes operators pattern_search possible predicate calculus expressions premise problem domain problem-solving production rules production system PROLOG propositional calculus reasoning recursive relationships represent representation language search algorithms search space Section semantic sentence shortest path solution path solver solving space graph space search strategy structure subgoals substitutions symbols techniques theorem theory tic-tac-toe tiles true truth value unification unify variable