Spontaneous Retrieval from Long-Term Memory for a Cognitive Architecture


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




spontaneous retrieval, missing link


This paper presents the first functional evaluation of spontaneous, uncued retrieval from long-term memory in a cognitive architecture. The key insight is that current deliberate cued retrieval mechanisms require the agent to have knowledge of when and what to retrieve --- knowledge that may be missing or incorrect. Spontaneous uncued retrieval eliminates these requirements through automatic retrievals that use the agent's problem solving context as a heuristic for relevance, thus supplementing deliberate cued retrieval. Using constraints derived from this insight, we sketch the space of spontaneous retrieval mechanisms and describe an implementation of spontaneous retrieval in Soar together with an agent that takes advantage of that mechanism. Empirical evidence is provided in the Missing Link word-puzzle domain, where agents using spontaneous retrieval out-perform agents without that capability, leading us to conclude that spontaneous retrieval can be a useful mechanism and is worth further exploration.




How to Cite

Li, J., & Laird, J. (2015). Spontaneous Retrieval from Long-Term Memory for a Cognitive Architecture. Proceedings of the AAAI Conference on Artificial Intelligence, 29(1). https://doi.org/10.1609/aaai.v29i1.9224



AAAI Technical Track: Cognitive Systems