One system for learning and remembering episodes and rules
Artificial Intelligence
2024-07-09 v1 Neural and Evolutionary Computing
Abstract
Humans can learn individual episodes and generalizable rules and also successfully retain both kinds of acquired knowledge over time. In the cognitive science literature, (1) learning individual episodes and rules and (2) learning and remembering are often both conceptualized as competing processes that necessitate separate, complementary learning systems. Inspired by recent research in statistical learning, we challenge these trade-offs, hypothesizing that they arise from capacity limitations rather than from the inherent incompatibility of the underlying cognitive processes. Using an associative learning task, we show that one system with excess representational capacity can learn and remember both episodes and rules.
Cite
@article{arxiv.2407.05884,
title = {One system for learning and remembering episodes and rules},
author = {Joshua T. S. Hewson and Sabina J. Sloman and Marina Dubova},
journal= {arXiv preprint arXiv:2407.05884},
year = {2024}
}