Functional Interactions Between Memory and Recognition Judgments

Authors

  • Justin Li University of Michigan
  • Nate Derbinsky University of Michigan
  • John Laird University of Michigan

DOI:

https://doi.org/10.1609/aaai.v26i1.8150

Keywords:

long term memory, recognition, cognitive architecture

Abstract

One issue facing agents that accumulate large bodies of knowledge is determining whether they have knowl- edge that is relevant to its current goals. Performing comprehensive searches of long-term memory in every situation can be computationally expensive and disrup- tive to task reasoning. In this paper, we demonstrate that the recognition judgment — a heuristic for whether memory structures have been previously perceived — can serve as a low-cost indicator of the existence of potentially relevant knowledge. We present an approach for computing both context-dependent and context- independent recognition judgments using processes and data shared with declarative memories. We then de- scribe an initial, efficient implementation in the Soar cognitive architecture and evaluate our system in a word sense disambiguation task, showing that it reduces the number of memory searches without degrading agent performance.

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Published

2021-09-20

How to Cite

Li, J., Derbinsky, N., & Laird, J. (2021). Functional Interactions Between Memory and Recognition Judgments. Proceedings of the AAAI Conference on Artificial Intelligence, 26(1), 228-234. https://doi.org/10.1609/aaai.v26i1.8150

Issue

Section

AAAI Technical Track: Cognitive Systems