Abstract. An optimal probabilistic-planning algorithm solves a problem, usually modeled by a Markov decision process, by finding its optimal policy. In this paper, we study the k ...
Partially observable Markov decision processes (POMDPs) are widely used for planning under uncertainty. In many applications, the huge size of the POMDP state space makes straightf...
Joni Pajarinen, Jaakko Peltonen, Ari Hottinen, Mik...
One-clock priced timed games is a class of two-player, zero-sum, continuous-time games that was defined and thoroughly studied in previous works. We show that One-clock priced ti...
Thomas Dueholm Hansen, Rasmus Ibsen-Jensen, Peter ...
ng-Lens Abstraction for Markov Decision Processes⋆ In Proc. of CAV 2007: 19th International Conference on Computer-Aided Verification, Lectures Notes in Computer Science. c Spri...
We present a new algorithm, called incremental least squares policy iteration (ILSPI), for finding the infinite-horizon stationary policy for partially observable Markov decision ...