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