Within epsilon of optimal play in the cultaptation social learning game

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Within epsilon of optimal play in the cultaptation social learning game

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International Conference on Autonomous Agents archive
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 table of contents

Budapest, Hungary

SESSION: Social/organizational aspects table of contents

Pages 1327-1328

Year of Publication: 2009

ISBN:978-0-9817381-7-8

Authors

Ryan Carr	University of Maryland, College Park, MD
Eric Raboin	University of Maryland, College Park, MD
Austin Parker	University of Maryland, College Park, MD
Dana Nau	University of Maryland, College Park, MD

Sponsors

: The Foundation for Intelligent Physical Agents
Microsoft Research : Microsoft Research
: Whitestein Technologies
: European Office of Aerospace Research and Development, Air Force Office of Scientific Research, United States Air Force Research Laboratory
: Drexel University
: Wiley -- Blackwell Ltd

Publisher

International Foundation for Autonomous Agents and Multiagent Systems Richland, SC

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ABSTRACT

Social learning, in which members of a society learn by observing the behavior of others, is an important foundation for human culture, and is observed in many other species as well. It seems natural to assume that social learning evolved due to the inherent superiority of copying others' success rather than learning on one's own via trial-and-error innovation. However, there has also been substantial work questioning this intuition [3, 5, 1, 6, 4]. For example, blindly copying information from others is not useful if the information is wrong---or if it once was right but has since become outdated. Under what conditions does social learning outperform trial-and-error learning, and what kinds of social-learning strategies are likely to perform well?

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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