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Learning in autonomous robots

Published online by Cambridge University Press:  07 July 2009

Henry Hexmoor  and
Lisa Meeden
Henry Hexmoor
Affiliation:
226 Bell Hall, Department of Computer Science, SUNY at Buffalo, Buffalo, NY 14260. USA. Email:[email protected]
Lisa Meeden
Affiliation:
Computer Science Program, Swarthmore College, 500 College Ave, Swarthmore, PA 19081, USA. Email:[email protected]
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Extract

The definitions above, separated by ten years, represent two very different conceptions of learning. For Simon learning depends on an internal change in representation, and for Kaelbling it is instead measured in terms of an external change in behaviour. Furthermore, Kaelbling's focus on the situatedness of the learning system being embedded in its environment reflects the recent experience gained by much direct experimentation with physical robots.

Type
Research Article
Information
The Knowledge Engineering Review , Volume 11 , Issue 4 , December 1996 , pp. 361 - 364
Copyright
Copyright © Cambridge University Press 1996

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References

Hexmoor, H and Meeden, L, eds, 1996. ROBOLEARN 96: An International Workshop on Learning for Autonomous Agents SUNY at Buffalo, Technical Report 96−11, Computer Science, Buffalo, NY. (Information about the workshop and related discussions can be obtained at: http://www.cs.buffalo.edu/-hexmoor/ robolearn96.html.)Google Scholar
Kaelbling, LP, 1993. Learning in Embedded Systems MIT Press.Google Scholar
Simon, H, 1983. “Why should machines learn?” In Carbonell, J, Michalski, R and Mitchell, T, eds, Machine Learning: An Artificia1 Intelligence Approach. Tioga Press, CA.Google Scholar