Name
Abstract | ||
|---|---|---|
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 maxmin control policy which achieves this probability. The modeling framework and computational algorithm are demonstrated using an example derived from a robust motion planning application. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/CDC.2011.6161218 | 2011 50TH IEEE CONFERENCE ON DECISION AND CONTROL AND EUROPEAN CONTROL CONFERENCE (CDC-ECC) |
Keywords | Field | DocType |
zero sum game,robust control,dynamic programming algorithm,dynamic programming,motion planning,irrigation,path planning,discrete time,argon,games,system dynamics,noise,computer model,computational modeling,dynamic game,probability,state space | Motion planning,Dynamic programming,Mathematical optimization,Control theory,Control theory,Computer science,Probabilistic logic,Discrete time and continuous time,Robust control,State space,Hybrid system | Conference |
ISSN | Citations | PageRank |
0743-1546 | 4 | 0.43 |
References | Authors | |
17 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Maryam Kamgarpour | 1 | 180 | 27.26 |
| Jerry Ding | 2 | 141 | 9.61 |
| Sean Summers | 3 | 178 | 12.10 |
| Alessandro Abate | 4 | 1098 | 94.52 |
| John Lygeros | 5 | 2742 | 319.22 |
| claire j tomlin | 6 | 1174 | 141.27 |