Networks of Learning Automata

1. Front Matter

   Pages i-xv

   PDF

2. Introduction

   • M. A. L. Thathachar, P. S. Sastry

   Pages 1-49

3. Games of Learning Automata

   • M. A. L. Thathachar, P. S. Sastry

   Pages 51-103

4. Feedforward Networks

   • M. A. L. Thathachar, P. S. Sastry

   Pages 105-138

5. Learning Automata for Pattern Classification

   • M. A. L. Thathachar, P. S. Sastry

   Pages 139-176

6. Parallel Operation of Learning Automata

   • M. A. L. Thathachar, P. S. Sastry

   Pages 177-204

7. Some Recent Applications

   • M. A. L. Thathachar, P. S. Sastry

   Pages 205-222

8. Epilogue

   • M. A. L. Thathachar, P. S. Sastry

   Pages 223-225

9. Back Matter

   Pages 227-268

   PDF

Networks of Learning Automata: Techniques for Online Stochastic Optimization is a comprehensive account of learning automata models with emphasis on multiautomata systems. It considers synthesis of complex learning structures from simple building blocks and uses stochastic algorithms for refining probabilities of selecting actions. Mathematical analysis of the behavior of games and feedforward networks is provided. Algorithms considered here can be used for online optimization of systems based on noisy measurements of performance index. Also, algorithms that assure convergence to the global optimum are presented. Parallel operation of automata systems for improving speed of convergence is described. The authors also include extensive discussion of how learning automata solutions can be constructed in a variety of applications.

• Computer Vision
• Performance
• Simulation
• Stochastic Approximation
• Stochastic Optimization
• algorithms
• calculus
• cognition
• communication
• intelligence
• learning
• optimization
• organization
• proving
• supervised learning

• Dept. of Electrical Engineering, Indian Institute of Science, Bangalore, India

  M. A. L. Thathachar, P. S. Sastry

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