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A Multi-Domain Evaluation of Scaling in a General Episodic Memory

Nate Derbinsky, Justin Li, John E. Laird

Year
2021
Citations
5
Access
Open access

Abstract

Episodic memory endows agents with numerous general cognitive capabilities, such as action modeling and virtual sensing. However, for long-lived agents, there are numerous unexplored computational challenges in supporting useful episodic-memory functions while maintaining real-time reactivity. In this paper, we review the implementation of episodic memory in Soar and present an expansive evaluation of that system. We demonstrate useful applications of episodic memory across a variety of domains, including games, mobile robotics, planning, and linguistics. In these domains, we characterize properties of environments, tasks, and episodic cues that affect performance, and evaluate the ability of Soar’s episodic memory to support hours to days of real-time operation.

Keywords

Episodic memorySoarSemantic memoryComputer scienceExpansiveArtificial intelligenceCognitive psychologyCognitive scienceReconstructive memoryHuman–computer interaction

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