Filtering as a reasoning-control strategy: An experimental assessment

In dynamic environments, optimal deliberation about what actions to perform is impossible. Instead, it is sometimes necessary to trade potential decision quality for decision timeliness. One approach to achieving this trade-off is to endow intelligent agents with meta-level strategies that provide them guidance about when to reason (and what to reason about) and when to act. We describe our investigations of a particular meta-level reasoning strategy, filtering, in which an agent commits to the goals it has already adopted, and then filters from consideration new options that would conflict with the successful completion of existing goals. To investigate the utility of filtering, a series of experiments was conducted using the Tileworld testbed. Previous experiments conducted by Kinny and Georgeff used an earlier version of the Tileworld to demonstrate the feasibility of filtering. Results are presented that replicate and extend those of Kinny and Georgeff and demonstrate some significant environmental influences on the value of filtering.