My research represents an approach to integrating planning and execution in time-sensitive environments. The primary focus is on a problem called continual on-line planning. New goals arrive stochastically during execution, the agent issues actions for execution one at a time, and the environment is otherwise deterministic. My dissertation will address this setting in three stages: optimizing total goal achievement time, handling on-line goal arrival during planning or execution, and adapting to changes in state also during planning or execution. My current approach to this problem is based on incremental heuristic search. The two central issues are the decision of which partial plans to elaborate during search and the decision of when to issue an action for execution. I have proposed an extension of Russell and Wefald's decision-theoretic A* algorithm that is not limited by assumptions of an admissible heuristic like DTA*. This algorithm, Decision Theoretic On-line Continual Search (DTOCS), handles the complexities of the on-line setting by balancing deliberative planning and real-time response.
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