Toward a Plan Steering Agent: Experiments with Schedule Maintenance

Tim Oates and Paul R. Cohen

When a plan involves hundreds or thousands of events over time it can be difficult or impossible to tell whether those events are unfolding "according to plan" and to assess the impact of dynamic plan modifications. Pathological states may arise in which goals cannot be attained or are attained too slowly. Plan steering is an agent-based approach to this problem. The agent monitors an unfolding plan, detects and predicts pathological situations, and develops dynamic plan modifications that will steer the plan around the problem. We present results for such a system that performs the related task of schedule maintenance in the transportation planning domain. The agent uses limited domain knowledge and simple heuristics and is able to improve throughput significantly.

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