Toward a Plan Steering Agent: Experiments with Schedule Maintenance

When a plan involves hundreds or thousands of events over time it can be di cult or impossible to tell whether those events are unfolding \according to plan" and to assess the impact of dynamic plan modi cations. 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 modi cations 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 signi cantly. 0 This research is supported by ARPA-AFOSR contract F30602-91-C-0076. 

• Type: Conference
• Year: 1994
• Where: AIPS
• Authors: Tim Oates, Paul R. Cohen
• Keywords: AIPS 1994, Artificial Intelligence, Dynamic Plan Modi, Plan Involves Hundreds, Plan Modi Cations