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 | 20 |
PART III | 25 |
Copyright | |
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Common terms and phrases
actions algorithm allows applied approach arcs argument artificial backtrack begin belief block called Chapter closed complexity concepts conceptual graphs conclusion consider cost create defined definition depth-first described determine direction discussed domain element engine evaluation examined example expert systems expression facts fail Figure formal function given gives goal graph heuristic human implement important indicates inference intelligence interpretation knowledge knowledge base language logical match meaning measures memory move natural nodes Note objects operators path performance planning possible predicate calculus premise presented problem problem-solving production system PROLOG propositional reasoning recursive relations relationships represent representation result rules semantic sentence simple situation solution solving space specific strategy structure substitutions symbols theory true truth unify variable