Thomas Wagner, Alan Garvey, Victor Lesser
Difficult real-time AI problems require a means for expressing multi-dimensional and dynamic goal criteria and a principled model for satisficing to best meet the criteria. In the context of the Design-to-Criteria task scheduling paradigm, we define a new general client specification metaphor for describing such complex goal criteria or utility attributes, and couple it with a principled evaluation model for using the criteria. The criteria specification and corresponding evaluation mechanism are used throughout the Design-to-Criteria scheduling process to focus scheduling activities on solutions and partial solutions that are most likely to meet the criteria, i.e., to result in the focused production of custom satisficing schedules. Examples of the power of the approach at reducing the complexity of the scheduling task and designing custom satisficing schedules, are shown.