Transfer learning through 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 andpossibly takes a long time. Here, knowledge transfer betweentasks is considered. In this paper, we argue that an abstraction c...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
2017
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/19465/ http://umpir.ump.edu.my/id/eprint/19465/1/Transfer%20Learning%20through%20Abstraction%20Using%20Learning%20Vector%20Quantization.pdf http://umpir.ump.edu.my/id/eprint/19465/2/Transfer%20Learning%20through%20Abstraction%20Using%20Learning%20Vector%20Quantization%201.pdf |
Internet
http://umpir.ump.edu.my/id/eprint/19465/http://umpir.ump.edu.my/id/eprint/19465/1/Transfer%20Learning%20through%20Abstraction%20Using%20Learning%20Vector%20Quantization.pdf
http://umpir.ump.edu.my/id/eprint/19465/2/Transfer%20Learning%20through%20Abstraction%20Using%20Learning%20Vector%20Quantization%201.pdf