PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Fast Reachability Analysis for Uncertain SSPs
Olivier Buffet
In: IJCAI 2005 Workshop on Planning and Learning in A Priori Unknown or Dynamic Domains, 1 Aug 2005, Edinburgh.


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, what can be checked easily for a certain SSP, and with a more complex algorithm for an uncertain SSP, i.e. where only a possible interval is known for each transition probability. This paper makes a simplified description of these two processes, and demonstrates how the time consuming uncertain analysis can be dramatically speeded up. The main improvement still needed is to turn to a symbolic analysis in order to avoid a complete state-space enumeration.

PDF - Requires Adobe Acrobat Reader or other PDF viewer.
EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Theory & Algorithms
ID Code:1710
Deposited By:Olivier Buffet
Deposited On:28 November 2005