Risk-Avoiding Reinforcement Learning
碩士 === 國立臺灣大學 === 資訊工程學研究所 === 99 === Traditional reinforcement learning agents focus on maximizing the expected cumulated rewards and ignore the distribution of the return. However, for some tasks people prefer actions that might not lead to as much return but more likely to avoid disaster. This th...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Others |
| Language: | en_US |
| Published: |
2011
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| Online Access: | http://ndltd.ncl.edu.tw/handle/11854708998176094577 |