Yannakakis, G. N. and Levine, J. and J. Hallam, J. and Papageorgiou, M. (2003) Performance, robustness and effort cost comparison of machine learning mechanisms in FlatLand. In: 11th IEEE Mediterranean Conference on Control and Automation (MED'03). UNSPECIFIED.
Full text not available in this repository. (Request a copy from the Strathclyde author)Abstract
This paper presents the first stage of research into a multi-agent complex environment, called “FlatLand” aiming at emerging complex and adaptive obstacle-avoidance and targetachievement behaviors by use of a variety of learning mechanisms. The presentation includes a detailed description of the FlatLand simulated world, the learning mechanisms used as well as an efficient method for comparing the mechanisms’ performance, robustness and required computational effort.
| Item type: | Book Section |
|---|---|
| ID code: | 32308 |
| Keywords: | back-propagation, genetic algorithms, machine learning, multi-agent, simulated worlds, Electronic computers. Computer science |
| Subjects: | Science > Mathematics > Electronic computers. Computer science |
| Department: | Faculty of Science > Computer and Information Sciences |
| Related URLs: | |
| Depositing user: | Pure Administrator |
| Date Deposited: | 26 Jul 2011 10:23 |
| Last modified: | 12 Mar 2012 11:30 |
| URI: | http://strathprints.strath.ac.uk/id/eprint/32308 |
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