An algorithm for probabilistic planning
Artificial Intelligence - Special volume on planning and scheduling
mGPT: a probabilistic planner based on heuristic search
Journal of Artificial Intelligence Research
Planning with durative actions in stochastic domains
Journal of Artificial Intelligence Research
Over-subscription planning with numeric goals
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Planning under continuous time and resource uncertainty: a challenge for AI
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
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My thesis topic is plan generation in temporal, parallel, probabilistic domains with oversubscribed goals. I have defined a framework that includes two novel extensions. First, the plans can include parallel steps that serve the same goal and increase the probability of success in addition to parallel steps that serve different goals and decrease execution time. Second, already executing plan steps can be terminated if doing so saves resources, to achieve more goals. My algorithm called CPOAO (Concurrent, Probabilistic, Oversubscription AO) can deal with these extensions. In this paper, I summarize the design and implementation of CPOAO and its associated heuristics, and propose a plan of research.