Markov decision processes (MDPs) and contingency planning (CP) are two widely used approaches to planning under uncertainty. MDPs are attractive because the model is extremely gen...
We dene the probabilistic planning problem in terms of a probability distribution over initial world states, a boolean combination of goal propositions, a probability threshold, ...
MostAI representations and algorithms for plan generation havenot included the concept of informationproducingactions (also called diagnostics, or tests, in the decision making li...
This paper presents an approach to artificial intelligence planning based on linear temporal logic (LTL). A simple and easy-to-use planning language is described, PDDL-K (Planning...
Marta Cialdea Mayer, Carla Limongelli, Andrea Orla...
Verification techniques like SAT-based bounded model checking have been successfully applied to a variety of system models. Applying bounded model checking to compositional proce...
Jun Sun 0001, Yang Liu 0003, Jin Song Dong, Jing S...