Abstract
Learning behaviors of the hierarchical structure stochastic automata operating in the general nonstationary multiteacher environment are considered. It is shown that convergence with probability 1 to the optimal path is ensured by a new learning algorithm which is an extended form of the relative reward strength algorithm.
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Baba, N., Mogami, Y. (2003). A New Learning Algorithm for the Hierarchical Structure Learning Automata Operating in the General Nonstationary Multiteacher Environment. In: Palade, V., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2003. Lecture Notes in Computer Science(), vol 2773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45224-9_151
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DOI: https://doi.org/10.1007/978-3-540-45224-9_151
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