Please use this identifier to cite or link to this item:
https://www.um.edu.mt/library/oar/handle/123456789/29600| Title: | Performance, robustness and effort cost comparison of machine learning mechanisms in FlatLand |
| Authors: | Yannakakis, Georgios N. Levine, John Hallam, John Papageorgiou, Markos |
| Keywords: | Machine learning Back propagation (Artificial intelligence) Genetic algorithms Multiagent systems Computer simulation |
| Issue Date: | 2003 |
| Publisher: | Mediterranean Control Association |
| Citation: | Yannakakis, G. N., Levine, J., Hallam, J., & Papageorgiou, M. (2003). Performance, robustness and effort cost comparison of machine learning mechanisms in FlatLand. 11th Mediterranean Conference on Control and Automation, Rhodes. 1-6. |
| 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 target achievement 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. |
| URI: | https://www.um.edu.mt/library/oar//handle/123456789/29600 |
| Appears in Collections: | Scholarly Works - InsDG |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Performance_robustness_and_effort_cost_comparison_of_machine_learning_mechanisms_in_FlatLand.pdf | 257.82 kB | Adobe PDF | View/Open |
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