PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Robust Planning with (L)RTDP
Olivier Buffet and Douglas Aberdeen
In: 19th International Joint Conference on Artificial Intelligence (IJCAI'05), 30 July - 5 August 2005, Edinburgh, Scotland, UK.


Stochastic Shortest Path problems (SSPs), a subclass of Markov Decision Problems (MDPs), can be efficiently dealt with using Real-Time Dynamic Programming (RTDP). Yet, MDP models are often uncertain (obtained through statistics or guessing). The usual approach is robust planning: searching for the best policy under the worst model. This paper shows how RTDP can be made robust in the common case where transition probabilities are known to lie in a given interval.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Theory & Algorithms
ID Code:1707
Deposited By:Olivier Buffet
Deposited On:28 November 2005