Modeling Autobiographical Memory for Believable Agents

Authors

  • Andrew Kope Western University
  • Caroline Rose Western University
  • Michael Katchabaw Western University

Keywords:

believable agents, memory model, Minecraft

Abstract

We present a multi-layer hierarchical connectionist network model for simulating human autobiographical memory in believable agents. Grounded in psychological theory, this model improves on previous attempts to model agents’ event knowledge by providing a more dynamic and non-deterministic representation of autobiographical memories. From this model, a Java-based proof-of-concept prototype system was created for use as an enabling technology in video games. This prototype was leveraged in the creation of a Minecraft modification (mod) implementation of the model that is able to demonstrate context-dependent recall and the effects of recency on memory recall. Wider implications of the model in agent and game design are discussed.

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Published

2021-06-30

How to Cite

Kope, A., Rose, C., & Katchabaw, M. (2021). Modeling Autobiographical Memory for Believable Agents. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 9(1), 23-29. Retrieved from https://ojs.aaai.org/index.php/AIIDE/article/view/12686