Hybrid probabilistic programs framework [5] is a variation of probabilistic annotated logic programming approach, which allows the user to explicitly encode the available knowledge...
In this paper we formalise compilation of the conjunctive bodies of a restricted class of Horn rules into updates on terminologies. This involves a pre-processing of the graphs re...
Markov Decision Processes are a powerful framework for planning under uncertainty, but current algorithms have difficulties scaling to large problems. We present a novel probabil...
—To efficiently solve challenging motion-planning problems with dynamics, this paper proposes treating motion planning not just as a search problem in a continuous space but as ...
Although many real-world stochastic planning problems are more naturally formulated by hybrid models with both discrete and continuous variables, current state-of-the-art methods ...
Carlos Guestrin, Milos Hauskrecht, Branislav Kveto...