This paper deals with a well known problem in AI planning: detecting and resolving conflicts in nonlinear plans. We sketch a theory of restricted conflict detection and resolution...
Validating distributed systems is particularly difficult, since failures may occur due to a correlated occurrence of faults in different parts of the system. This paper describes ...
Michel Cukier, Ramesh Chandra, David Henke, Jessic...
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...
In our experiments with four well-known systems for solving partially observable planning problems (Contingent-FF, MBP, PKS, and POND), we were greatly surprised to find that they...
Ronald Alford, Ugur Kuter, Dana S. Nau, Elnatan Re...
Abstract— We propose a planning algorithm that allows usersupplied domain knowledge to be exploited in the synthesis of information feedback policies for systems modeled as parti...
Salvatore Candido, James C. Davidson, Seth Hutchin...