| Literature DB >> 33454217 |
Ishita Dasgupta1, Samuel J Gershman2.
Abstract
Computer scientists have long recognized that naive implementations of algorithms often result in a paralyzing degree of redundant computation. More sophisticated implementations harness the power of memory by storing computational results and reusing them later. We review the application of these ideas to cognitive science, in four case studies (mental arithmetic, mental imagery, planning, and probabilistic inference). Despite their superficial differences, these cognitive processes share a common reliance on memory that enables efficient computation.Entities:
Keywords: amortization; inference; memory; mental arithmetic; mental imagery; planning
Mesh:
Year: 2021 PMID: 33454217 DOI: 10.1016/j.tics.2020.12.008
Source DB: PubMed Journal: Trends Cogn Sci ISSN: 1364-6613 Impact factor: 20.229