Adaptive control of Markov processes with incomplete state information and unknown parameters |
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| Authors: | O Hernandez-Lerma S I Marcus |
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| Institution: | (1) Departamento de Matemáticas, Centro de Investigación del IPN, México, DF, Mexico;(2) Department of Electrical and Computer Engineering, University of Texas at Austin, Austin, Texas |
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| Abstract: | Recent results for parameter-adaptive Markov decision processes (MDP's) are extended to partially observed MDP's depending on unknown parameters. These results include approximations converging uniformly to the optimal reward function and asymptotically optimal adaptive policies.This research was supported in part by the Consejo del Sistema Nacional de Educación Tecnologica (COSNET) under Grant 178/84, in part by the Air Force Office of Scientific Research under Grant AFOSR-84-0089, in part by the National Science Foundation under Grant ECS-84-12100, and in part by the Joint Services Electronics Program under Contract F49602-82-C-0033. |
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| Keywords: | Partially observed Markov decision processes unknown parameters discounted reward criterion adaptive I-policies non-stationary value iteration principle of estimation and control |
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