Toward Combining Domain Theory and Recipes in Plan Recognition

Rogelio Enrique Cardona-Rivera, Robert Michael Young

Abstract: We present a technique to further narrow the gap between recipe-based and domain theory-based plan recognition through decompositional planning, a planning model that combines hierarchical reasoning as used in hierarchical task networks, and least-commitment refinement reasoning as used in partial-order causal link planning. We represent recipes through decompositional planning operators and use them to compile observed agent actions into an incomplete decompositional plan that represents them; this plan can then be input to a decompositional planner to identify the recognized plan-space plan. Our model thus synthesizes the heretofore disparate recipe-based and domain theory-based plan recognition variants into a unified knowledge representation and reasoning model.