Author name cluster

Susan Fox

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

2 papers

1 author row

IJCAI Conference 1995 Conference Paper

Using Introspective Reasoning to Refine Indexing

Susan Fox
David B. Leake

Introspective reasoning about a system's own reasoning processes can form the basis for learning to refine those reasoning processes. The ROBBIE1 system uses introspective reasoning to monitor the retrieval process of a case-based planner to detect retrieval of inappropriate cases. When retrieval problems are detected, the source of the problems is explained and the explanations are used to determine new indices to use during future case retrieval. The goal of ROBBIE's learning is to increase its ability to focus retrieval on relevant cases, with the aim of simultaneously decreasing the number of candidates to consider and increasing the likelihood that the system will be able to successfully adapt the retrieved cases to fit the current situation. We evaluate the benefits of the approach in light of empirical results examining the effects of index learning in the ROBBIE system.

PDF

AAAI Conference 1994 Short Paper

Introspective Reasoning in a Case-Based Planner

Susan Fox

Many current AI systems assume that the reasoning mechanisms used to manipulate their knowledge may be fixed ahead of time by the designer. This assumption may break down in complex domains. The focus of this research is developing a model of introspective reasoning and learning to enable a system to improve its own reasoning as well as its domain knowledge. Our model is based on the proposal of (Birnbaum et al. 1991) to use a model of the ideal behavior of a case-based system to judge system performance and to refine its reasoning mechanisms; it also draws on the research of (Ram and Cox 1994) on introspective failure-driven learning.

PDF Details