A key obstacle hampering fielding of AI planning applications is the considerable expense of developing, verifying, updating, and maintaining the planning knowledge base (KB). Planning systems must be able to compare favorably in terms of software lifecycle costs to other meansof automation such as scripts or rule-based expert systems. Consequently,in order to field real systems, planning
Steve A. Chien