Many current heuristics for domain-independent planning, such as Bonet and Geffner's additive heuristic and Hoffmann and Nebel's FF heuristic, are based on delete relaxa...
Probabilistic AI planning methods that minimize expected execution cost have a neutral attitude towards risk. We demonstrate how one can transform planning problems for risk-sensi...
Probabilistic planning problems are typically modeled as a Markov Decision Process (MDP). MDPs, while an otherwise expressive model, allow only for sequential, non-durative action...
Physical domains are notoriously hard to model completely and correctly, especially to capture the dynamics of the environment. Moreover, since environments change, it is even mor...
The FF relaxed plan heuristic is one of the most effective techniques in domain-independent satisficing planning and is used by many state-of-the-art heuristic-search planners. Ho...