Knowledge acquisition techniques for a military planning system

Abstract

In order to build realistic AI planning systems, it is necessary to develop sophisticated tools for knowledge acquisition. This paper describes two knowledge acquisition tools for a crisis action planning system. The first is a graphical operator editor that enables users to develop new planning operators and revise existing operators. The second is an inductive learning system, based on the PAGODA learning model, that learns from simulator feedback and from choices made by the user during planning. This paper describes the work done so far, and proposed for the future, on these tools.<>