Reinforcement Learning Hardware Accelerator using Cache-Based Memoization for Optimized Q-Table Selection
Author:
Affiliation:
1. Bandung Institute of Technology,Faculty of Industrial Technology,Indonesia
2. Bandung Institute of Technology,School of Electrical Engineering and Informatics,Indonesia
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10531139/10531159/10531164.pdf?arnumber=10531164
Reference17 articles.
1. Self-punishment and reward backfill for deep q-learning;Bonyadi,2023
2. Q-Learning in Continuous State and Action Spaces
3. Playing atari with deep reinforcement learning;Mnih,2013
4. Policy gradient fuzzy reinforcement learning
5. Provable benefits of actor-critic methods for offline reinforcement learning;Zanette,2021
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