Using Grice's maxim of Quantity to select the content of plan descriptions

Intelligent systems 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, I present the Cooperative Plan Identi cation (CPI) architecture, a computational model that generates concise, e ective textual descriptions of plans. In this model, speakers and hearers cooperate with one another in their communication about a plan. A hearer interprets a concise plan description by lling in the missing detail using plan reasoning. A cooperative speaker selects the content of a plan description based on his expectation that the hearer is able to complete the description in much the same way that a planning system completes a partial plan. The architecture has been empirically evaluated in an experiment, also described here, in which subjects following instructions produced by the CPI architecture performed their tasks with fewer execution errors and achieved a higher percentage of their tasks' goals than did subjects following instructions produced by alternative methods.