Transformational Planning of Reactive Behavior
YALE UNIV NEW HAVEN CT DEPT OF COMPUTER SCIENCE
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Reactive plans are plans that include steps for sensing the world and coping with the data so obtained. We investigate the application of AI planning techniques to plans of this sort in a simple simulated world. To achieve fast reaction times, we assume that the agent starts with a default reactive plan, while the planner attempts to improve it by applying plan transformations, thus searching through the space of transformed plans. When the planner has what it believes to be a better plan, it swaps the new plan into the agents controller. The plans are written in a reactive language that allows for this kind of swapping. The language allows for concurrency, and hence, truly nonlinear plans. The planner evaluates plans by projecting them, that is, generating scenarios for how execution might go. The resulting projections give estimates of plan values, but also provide clues to how the plan might be improved. These clues are unearthed by critics that go through the scenario sets, checking how the world state and the agent state evolved. The critics suggest plan transformations with associated estimates of how much they will improve the plan.
- Computer Programming and Software