Early Warnings of Plan Failure, False Positives and Envelopes, Experiments and a Model

TR Title:Common Lisp Relational Table Manager (RTM) Users Manual Author: Paul E. Silvey Address: Computer Science Department, LGRC University of Massachusetts Box 34610 Amherst, MA 01003-4610 Date: December 1992 RTM is a relational database management extension to Common Lisp. It provides capabilities for creating named tables with named column attributes of specified types (domains). Data access and manipulation is accomplished using a functional interface modeled after the database industry standard Structured Query Language (SQL). #92-20 - Paul R. Cohen, Robert St. Amant, David M. Hart: Early Warnings of Plan Failure, False Positives and Envelopes: Experiments and a Model. We analyze a tradeoff between early warnings of plan failures and false positives. In general, a decision rule that provides earlier warnings will also produce more false positives. Slack time envelopes are decision rules that warn of plan failures in our Phoenix system. Until now, they have been constructed according to ad hoc criteria. In this paper we show that good performance under different criteria can be achieved by slack time envelopes throughout the course of a plan, even though envelopes are very simple decision rules. We also develop a probabilistic model of plan progress, from which we derive an algorithm for constructring slack time envelopes that achieve desired tradeoffs betwen early warnings and false positives. #92-42 - Adele E. Howe: Analyzing Failure Recovery to Improve Planner Design. Plans fail for many reasons. During planner development, failure can often be traced to actions of the planner itself. Failure recovery analysis is a procedure for analyzing execution traces of failure recovery to discover how the planner''s actions may be causing failures. The four step procedure involves statistically analyzing execution data for dependencies between actions and failures, mapping those dependencies to plan structures, explaining how the structures might produce the observed dependencies, and recommending modifications. The procedure is demonstrated by applying it to explain how a particular recovery action may lead to a particular failure in the Phoenix planner. The planner is modified based on the recommendations of the analysis, and the modifications are shown to improve the planner''s performance by removing a source of failure and so reducing the overall incidence of failure.