Networks of Learning Automata [electronic resource] : Techniques for Online Stochastic Optimization /

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.

Bibliographic Details

Main Authors:	Thathachar, M. A. L. author., Sastry, P. S. author., SpringerLink (Online service)
Format:	Texto biblioteca
Language:	eng
Published:	Boston, MA : Springer US : Imprint: Springer, 2004
Subjects:	Physics., Operations research., Decision making., Computer science., Artificial intelligence., Computational linguistics., Statistical physics., Dynamical systems., Statistical Physics, Dynamical Systems and Complexity., Artificial Intelligence (incl. Robotics)., Language Translation and Linguistics., Operation Research/Decision Theory., Computer Science, general.,
Online Access:	http://dx.doi.org/10.1007/978-1-4419-9052-5
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