The Use of Condition Types to Restrict Search in an AI Planner

Austin Tate, Brian Drabble, Jeff Dalton

Condition satisfaction in planning has received a great deal of experimental and formal attention. A "Truth Criterion" lies at the heart of many planners and is critical to their capabilities and performance. However, there has been little study of ways in which the search space of a planner incorporating such a Truth Criterion can be guided. The aim of this document is to give a description of the use of condition "type" information to inform the search of an AI planner and to guide the production of answers by a planner’s truth criterion algorithm. The authors aim to promote discussion on the merits or otherwise of using such domain-dependent condition type restrictions as a means to communicate valuable information from the domain writer to a general purpose domain-independent planner.


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