Transfer learning through policy abstraction using learning vector quantization
Reinforcement learning (RL) enables an agent to find a solution to a problem by interacting with the environment. However, the learning process always starts from scratch and possibly takes a long time. Here, knowledge transfer between tasks is considered. In this paper, we argue that an abstraction...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
UTeM
2018
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/21033/1/Transfer%20learning%20through%20policy%20abstraction.pdf |