TY - GEN
T1 - Caching Algorithms and Rational Models of Memory
AU - Press, Avi
AU - Pacer, Michael
AU - Griffiths, Thomas L.
AU - Christian, Brian
N1 - Funding Information:
Acknowledgments. This work was supported by grant number SMA-1228541 from the National Science Foundation.
Publisher Copyright:
© 2014 Proceedings of the 36th Annual Meeting of the Cognitive Science Society, CogSci 2014. All rights reserved.
PY - 2014
Y1 - 2014
N2 - People face a problem similar to that faced by algorithms that manage the memory of computers: trying to organize information to maximize the chance it will be available when needed in the future. In computer science, this problem is known as “caching”. Inspired by this analogy, we compared the properties of a model of human memory proposed by Anderson and Schooler (1991) and caching algorithms used in computer science. We tested each algorithm on a dataset relevant to human cognition: headlines from the New York Times. In addition to overall performance, we investigated whether the algorithms from computer science replicated the well-documented effects of recency, practice, and spacing on human memory. Anderson and Schooler's model performed comparably to the worst caching algorithms, but was the only model that captured the spacing effects seen in human memory data. All models showed similar effects of recency and practice.
AB - People face a problem similar to that faced by algorithms that manage the memory of computers: trying to organize information to maximize the chance it will be available when needed in the future. In computer science, this problem is known as “caching”. Inspired by this analogy, we compared the properties of a model of human memory proposed by Anderson and Schooler (1991) and caching algorithms used in computer science. We tested each algorithm on a dataset relevant to human cognition: headlines from the New York Times. In addition to overall performance, we investigated whether the algorithms from computer science replicated the well-documented effects of recency, practice, and spacing on human memory. Anderson and Schooler's model performed comparably to the worst caching algorithms, but was the only model that captured the spacing effects seen in human memory data. All models showed similar effects of recency and practice.
KW - caching algorithms
KW - memory
KW - rational analysis
UR - http://www.scopus.com/inward/record.url?scp=85095262469&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85095262469&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85095262469
T3 - Proceedings of the 36th Annual Meeting of the Cognitive Science Society, CogSci 2014
SP - 1198
EP - 1203
BT - Proceedings of the 36th Annual Meeting of the Cognitive Science Society, CogSci 2014
PB - The Cognitive Science Society
T2 - 36th Annual Meeting of the Cognitive Science Society, CogSci 2014
Y2 - 23 July 2014 through 26 July 2014
ER -