Algorithms and architectures of artificial intelligence

Title page......Page 1
Contents......Page 7
Introduction......Page 11
Language of algorithms......Page 13
Knowledge Handling......Page 15
Abstract representation of knowledge systems......Page 16
Examples of deductive systems......Page 18
Brute force deduction and value propagation......Page 21
Language......Page 22
Inference rule - resolution......Page 24
Pure Prolog......Page 25
Nonmonotonic theories......Page 27
Production rules......Page 29
Decision tables......Page 31
Rete algorithm......Page 32
Semantic networks......Page 35
Frames......Page 37
Hierarchical connection......Page 39
Semantic connection......Page 40
Union......Page 41
Examples of knowledge architectures......Page 42
Ontologies and knowledge systems......Page 44
Summary......Page 45
Exercises......Page 48
Search......Page 51
Search problem......Page 52
Breadth-first search......Page 54
Depth-first search......Page 56
Search on binary trees......Page 57
Best-first search......Page 58
Beam search......Page 59
Hill-climbing......Page 60
Constrained hill-climbing......Page 61
Search with backtracking......Page 62
Search on and-or trees......Page 63
Search with dependency-directed backtracing......Page 64
Branch-and-bound search......Page 65
Stochastic branch and bound search......Page 66
Minimax search......Page 67
Alpha-beta pruning......Page 68
A* algorithm......Page 70
Unification......Page 72
Dictionary search......Page 73
Simulated annealing......Page 75
Discrete dynamic programming......Page 78
Viterby algorithms......Page 80
Forward search and backward search......Page 82
Hierarchy of search methods......Page 83
Exercises......Page 85
Learning and Decision Making......Page 89
Parametric learning......Page 90
Adaptive automata......Page 91
Concept learning as search in a hypothesis space......Page 94
Specific to general concept learning......Page 96
General to specific concept learning......Page 98
Inductive inference......Page 100
Learning with an oracle......Page 101
Inductive logic programming......Page 102
Learning by inverting resolution......Page 104
Massively parallel learning in genetic algorithms......Page 108
Learning in neural nets......Page 110
Perceptrons......Page 112
Hopfield nets......Page 113
Hamming nets......Page 114
Carpenter-Grossberg classifier......Page 116
Bayesian networks......Page 119
Taxonomy of neural nets......Page 122
Data clustering......Page 123
K-means clustering......Page 124
Learning decision trees from examples......Page 126
Learning productions from examples......Page 129
Discovering regularities in monotonous systems......Page 130
Discovering relations and structure......Page 133
Summary......Page 135
Exercises......Page 137
Problem Solving and Planning......Page 139
Constraint satisfaction problem......Page 140
Binary consistency......Page 142
Path  consistency......Page 143
Functional constraint networks......Page 144
Computational problems and value propagation......Page 145
Equational problem-solver......Page 147
Minimizing an algorithm......Page 149
Higher-order constraint propagation......Page 150
Clustering of equations......Page 155
Interval propagation......Page 158
Deductive synthesis of programs......Page 159
Transformational synthesis of programs......Page 160
Structural synthesis of programs......Page 161
Planning......Page 163
Intelligent agents......Page 165
Agent architectures......Page 166
Agent communication languages......Page 169
Implementation of agents......Page 170
Reflection......Page 171
Exercises......Page 173
References......Page 177
Subject Index......Page 179