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Published in:
2005 | OriginalPaper | Chapter
New Learning Algorithm for Hierarchical Structure Learning Automata Operating in P-Model Stationary Random Environment
Author : Yoshio Mogami
Published in: Computational Intelligence and Security
Publisher: Springer Berlin Heidelberg
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In this paper, based on the concept of Discretized Generalized Pursuit Algorithm (DGPA), the discretized generalized pursuit hierarchical structure learning algorithm is constructed which is applied to the hierarchical structure learning automata oprating in the P-model stationary random environment. The efficacy of our algorithm is demonstrated by the numerical simulation, in which the hierarchical structure learning automata is applied to the problem of the mobile robots going through an unknown maze (the maze passage problem of mobile robots).