Discrete time stochastic hybrid dynamical games: Verification & controller synthesis

This paper presents a framework for analyzing probabilistic safety and reachability problems for discrete time stochastic hybrid systems in scenarios where system dynamics are affected by rational competing agents. In particular, we consider a zero-sum game formulation of the probabilistic reach-avo...

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Bibliographic Details
Main Authors: Kamgarpour, M., Ding, J., Summers, S., Abate, A., Lygeros, J., Tomlin, C.
Format: Conference Proceeding
Language:English
Subjects:
Argon
Computational modeling
Europe
Games
Irrigation
Noise
Numerical models
Online Access:Request full text
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Summary:This paper presents a framework for analyzing probabilistic safety and reachability problems for discrete time stochastic hybrid systems in scenarios where system dynamics are affected by rational competing agents. In particular, we consider a zero-sum game formulation of the probabilistic reach-avoid problem, in which the control objective is to maximize the probability of reaching a desired subset of the hybrid state space, while avoiding an unsafe set, subject to the worst-case behavior of a rational adversary. Theoretical results are provided on a dynamic programming algorithm for computing the maximal reach-avoid probability under the worst-case adversary strategy, as well as the existence of a max-min control policy which achieves this probability. The modeling framework and computational algorithm are demonstrated using an example derived from a robust motion planning application.
ISSN:0191-2216
DOI:10.1109/CDC.2011.6161218