Abstract
In this paper a method of adaptive selection of helper-objectives in evolutionary algorithms, which was previously applied to model problems only, is applied to generation of test cases for programming challenge tasks. The method is based on reinforcement learning. Experiments show that the proposed method performs equally well compared to the best helper-objectives selected by hand.
| Original language | English |
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| Title of host publication | Proceedings of the IEEE Congress on Evolutionary Computation |
| Subtitle of host publication | CEC 2013, Cancun, Mexico, June 20-23, 2013. |
| Publisher | IEEE Press |
| Pages | 2245-2250 |
| Number of pages | 6 |
| ISBN (Print) | 9781479904532, 1479904538 |
| DOIs | |
| Publication status | Published - 20 Jun 2013 |
| Externally published | Yes |
| Event | 2013 IEEE Congress on Evolutionary Computation (CEC) - Cancun, Mexico Duration: 20 Jun 2013 → 23 Jun 2013 |
Conference
| Conference | 2013 IEEE Congress on Evolutionary Computation (CEC) |
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| Country/Territory | Mexico |
| City | Cancun |
| Period | 20 Jun 2013 → 23 Jun 2013 |