COMMON-SENSICAL INCENTIVE REWARD IN DEEP ACTOR-CRITIC REINFORCEMENT LEARNING FOR MOBILE ROBOT NAVIGATION
Recently, various Deep Actor-Critic Reinforcement Learning (DAC-RL) algorithms have been widely utilized for training mobile robots in acquiring navigational policies. However, they usually need a preventively long learning time to achieve good policies. This research proposes a two-stage training m...
| Published in: | International Journal of Innovative Computing, Information and Control |
|---|---|
| Main Author: | |
| Format: | Article |
| Language: | English |
| Published: |
ICIC International
2024
|
| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85186911357&doi=10.24507%2fijicic.20.02.373&partnerID=40&md5=1b41795e03a07d1af74236f5854d811a |