Learning Automata (eBook)

Front Cover 
1 
Learning Automata: Theory and Applications 4
Copyright Page 
5 
Table of Contents 
6 
Preface 10
Notations 14
Introduction 16
Chapter 1. Basic Notions and Definitions 
19 
Introduction 19
1 Controlled finite system 20
2 Control strategies 20
3 Dynamic characteristics of controlled finite system 23
4 Classification of controlled finite systems and their structures 24
5 Adaptive strategies and learning automata 28
6 Classification of problems of adaptive control of finite systems 29
Chapter 2. Reinforcement Schemes for Average Loss Function Minimization 32
Introduction 32
1 Adaptive control of static systems 33
2 Adaptive control of static systems and linear programming problem 37
3 Reinforcement schemes 41
4 Properties of reinforcement schemes 45
Chapter 3. Behaviour of Learning Automata for Different Reinforcement Schemes 53
Introduction 53
1 Reinforcement scheme of Narendra-Shapiro 54
2 Reinforcement scheme of Luce and Varshavskii-Vorontsova 65
3 Bush-Mosteller reinforcement scheme 72
4 Projectional stochastic approximation algorithm 80
Conclusion 88
Chapter 4. Multilevel Systems of Automata 90
Introduction 90
1 Hierarchical systems 90
2 The connection between two-level adaptive control and bilinear programming problem 91
3 Two-level hierarchical system of learning automata 95
4 Two-level hierarchical system of learning automata using a projectional stochastic approximation algorithm 106
5 Two-level hierarchical system with transmission of current information to the lower level 113
6 Multilevel hierarchical learning system 121
Conclusion 132
Chapter 5. Multimodal Function Optimization Using Learning Automata 133
Introduction 133
1 Optimization using a single learning automata 134
2 Optimization using a two-level hierarchical system of learning automata 141
3 Optimization using a multilevel learning automata system 149
Conclusion 156
Chapter 6. Applications of Learning Automata 157
Introduction 157
1 Practical aspects 161
2 Multilevel learning control of a drying furnace 163
3 Hierarchical learning control of an absorption column 176
4 Learning control of an evaporator 186
5 Adaptive choice of cyclic code in communications systems 191
6 Optimization of multimodal functions (without constraints 195
7 Optimization in presence of constraints 199
8 Application of learning automaton to neural network synthesis 212
Conclusion 216
Nomenclature 217
References 219
Appendix 228
Index 237