Algorithms and architectures of artificial intelligence

This book gives an overview of methods developed in artificial intelligence for search, learning, problem solving and decision-making. It gives an overview of algorithms and architectures of artificial intelligence that have reached the degree of maturity when a method can be presented as an algorit...

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Bibliographic Details
Main Author: Tyugu, Enn
Format: eBook Book
Language:English
Published: Amsterdam IOS Press 2007
SAGE Publications, Limited
Edition:1
Series:Frontiers in artificial intelligence and applications
Subjects:
ISBN:9781586037703, 1586037706
Online Access:Get full text
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Table of Contents:
  • Title page -- Contents -- Introduction -- Language of algorithms -- Knowledge Handling -- Knowledge and knowledge systems -- Abstract representation of knowledge systems -- Examples of deductive systems -- Brute force deduction and value propagation -- Clausal calculi and resolution -- Language -- Inference rule - resolution -- Resolution strategies -- Pure Prolog -- Nonmonotonic theories -- Production rules -- Decision tables -- Rete algorithm -- Semantic networks -- Frames -- Knowledge architecture -- Hierarchical connection -- Semantic connection -- Union -- Operational connection -- Examples of knowledge architectures -- Ontologies and knowledge systems -- Summary -- Exercises -- Search -- Search problem -- Exhaustive search methods -- Breadth-first search -- Depth-first search -- Search on binary trees -- Heuristic search methods -- Best-first search -- Beam search -- Hill-climbing -- Constrained hill-climbing -- Search with backtracking -- Search on and-or trees -- Search with dependency-directed backtracing -- Branch-and-bound search -- Stochastic branch and bound search -- Minimax search -- Alpha-beta pruning -- Specific search methods -- A* algorithm -- Unification -- Dictionary search -- Simulated annealing -- Discrete dynamic programming -- Viterby algorithms -- Forward search and backward search -- Hierarchy of search methods -- Exercises -- Learning and Decision Making -- Learning for adaptation -- Parametric learning -- Adaptive automata -- Symbolic learning -- Concept learning as search in a hypothesis space -- Specific to general concept learning -- General to specific concept learning -- Inductive inference -- Learning with an oracle -- Inductive logic programming -- Learning by inverting resolution -- Massively parallel learning in genetic algorithms -- Learning in neural nets -- Perceptrons -- Hopfield nets -- Hamming nets
  • Comparator -- Carpenter-Grossberg classifier -- Kohonen's feature maps -- Bayesian networks -- Taxonomy of neural nets -- Data clustering -- Sequential leader clustering -- K-means clustering -- Specific learning algorithms -- Learning decision trees from examples -- Learning productions from examples -- Discovering regularities in monotonous systems -- Discovering relations and structure -- Summary -- Exercises -- Problem Solving and Planning -- Constraint satisfaction problem -- Consistency algorithms -- Binary consistency -- Path consistency -- Propagation algorithms -- Functional constraint networks -- Computational problems and value propagation -- Equational problem-solver -- Minimizing an algorithm -- Lattice of problems on functional constraint network -- Higher-order constraint propagation -- Special algorithms of constraint solving -- Clustering of equations -- Interval propagation -- Program synthesis -- Deductive synthesis of programs -- Inductive synthesis of programs -- Transformational synthesis of programs -- Structural synthesis of programs -- Planning -- Scheduling -- Intelligent agents -- Agent architectures -- Agent communication languages -- Implementation of agents -- Reflection -- Exercises -- References -- Subject Index