MazeCov-Q: An Efficient Maze-Based Reinforcement Learning Accelerator for Coverage
Author:
Affiliation:
1. School of Electrical Engineering and Informatics, Bandung Institute of Technology,Indonesia
2. University Center of Excellence on Microelectronics, Bandung Institute of Technology,Indonesia
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10121902/10121921/10122120.pdf?arnumber=10122120
Reference14 articles.
1. Control System for Mobile Robot using FPGA-Based Q-Learning Accelerator
2. Design of Testing Environment for Line-Follower Robot with Obstacles
3. QTAccel: A Generic FPGA based Design for Q-Table based Reinforcement Learning Accelerators
4. PPCPP: A Predator–Prey-Based Approach to Adaptive Coverage Path Planning
5. Predator-Prey Reward Based Q-Learning Coverage Path Planning for Mobile Robot
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1. Reinforcement Learning Hardware Accelerator using Cache-Based Memoization for Optimized Q-Table Selection;2024 IEEE Symposium in Low-Power and High-Speed Chips (COOL CHIPS);2024-04-17
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