Cooperative Plan Identification: Constructing Concise and Effective Plan Descriptions

Abstract

Intelligent agents are often called upon to form plans that direct their own or other agents ’ activities. For these systems, the ability to describe plans to people in natural ways is an essential aspect of their interface. In this paper, we present the Cooperative Plan Identifi-cation (CPI) architecture, a computational model that generates concise, effective textual descriptions of plan data structures. The model incorporates previous theo-retical work on the comprehension of plan descriptions, using a generate-and-test approach to perform efficient search through the space of candidate descriptions. We describe an empirical evaluation of the CPI archi-tecture in which subjects following instructions pro-duced by the CPI architecture performed their tasks with fewer execution errors and achieved a higher per-centage of their tasks ’ goals than did subjects following instructions produced by alternative methods.