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Risk-Averse Planning Under Uncertainty

Ahmadi, Mohamadreza and Ono, Masahiro and Ingham, Michel D. and Murray, Richard M. and Ames, Aaron D. (2019) Risk-Averse Planning Under Uncertainty. . (Unpublished) https://resolver.caltech.edu/CaltechAUTHORS:20200109-092433424

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Abstract

We consider the problem of designing policies for partially observable Markov decision processes (POMDPs) with dynamic coherent risk objectives. Synthesizing risk-averse optimal policies for POMDPs requires infinite memory and thus undecidable. To overcome this difficulty, we propose a method based on bounded policy iteration for designing stochastic but finite state (memory) controllers, which takes advantage of standard convex optimization methods. Given a memory budget and optimality criterion, the proposed method modifies the stochastic finite state controller leading to sub-optimal solutions with lower coherent risk.


Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription
http://arxiv.org/abs/1909.12499arXivDiscussion Paper
ORCID:
AuthorORCID
Ahmadi, Mohamadreza0000-0003-1447-3012
Murray, Richard M.0000-0002-5785-7481
Ames, Aaron D.0000-0003-0848-3177
Record Number:CaltechAUTHORS:20200109-092433424
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20200109-092433424
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:100583
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:09 Jan 2020 18:05
Last Modified:09 Jan 2020 18:05

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