DocumentCode
2245136
Title
Observation-based performance sensitivity analysis for POMDPs
Author
Ji, Zhe ; Jiang, Xiaofeng ; Xi, Hongsheng
Author_Institution
Department of Auto, School of Information Science and Technology, University of Science and Technology of China, 230027, Hefei, China
fYear
2015
fDate
28-30 July 2015
Firstpage
1671
Lastpage
1676
Abstract
In this paper, the performance sensitivity analysis for Markov decision processes (MDPs) are generalized to study the partially observable Markov decision processes (POMDPs). The performance derivative formula and the performance difference formula based on observation are derived in this paper. The derivation does not need any overly strict assumptions. In order to find the optimal policy based on observation, an observation-based policy iteration algorithm is designed. An example is presented to show the applicability of the algorithm finally.
Keywords
Algorithm design and analysis; Approximation algorithms; Markov processes; Mathematical model; Optimization; Sensitivity analysis; Steady-state; POMDPs; Performance derivative formula; Performance difference formula; Performance sensitivity analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Conference (CCC), 2015 34th Chinese
Conference_Location
Hangzhou, China
Type
conf
DOI
10.1109/ChiCC.2015.7259887
Filename
7259887
Link To Document