Integrating Multiple Policies for Person-Following Robot Training Using Deep Reinforcement Learning
Given a training environment which follows Markov decision process for a specific task, a deep reinforcement learning (DRL) agent is able to find possible optimal policies which map states of the environment to appropriate actions by repeatedly trying various actions to maximize training rewards. Ho...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2021-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9437214/ |