PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Reachability Analysis for Uncertain SSPs
Olivier Buffet
In: 17th IEEE International Conference on Tools with Artificial Intelligence, 14-16 Nov 2005, Hong-Kong, China.

Abstract

Stochastic Shortest Path problems (SSPs) can be efficiently dealt with by the Real-Time Dynamic Programming algorithm (RTDP). Yet, RTDP requires that a goal state is always reachable. This paper presents an algorithm checking for goal reachability, especially in the complex case of an uncertain SSP where only a possible interval is known for each transition probability. This gives an analysis method for determining if SSP algorithms such as RTDP are applicable, even if the exact model is not known. We aim at a symbolic analysis in order to avoid a complete state-space enumeration.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Theory & Algorithms
ID Code:1708
Deposited By:Olivier Buffet
Deposited On:28 November 2005