An Efficient Hardware Implementation of Reinforcement Learning: The Q-Learning Algorithm

An Efficient Hardware Implementation of Reinforcement Learning: The Q-Learning Algorithm

In this paper we propose an efficient hardware architecture that implements the Q-Learning algorithm, suitable for real-time applications. Its main features are low-power, high throughput and limited hardware resources. We also propose a technique based on approximated multipliers to reduce the hard...

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Bibliographic Details
Main Authors: Sergio Spano, Gian Carlo Cardarilli, Luca Di Nunzio, Rocco Fazzolari, Daniele Giardino, Marco Matta, Alberto Nannarelli, Marco Re
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Artificial intelligence
hardware accelerator
machine learning
Q-learning
reinforcement learning
SARSA
Online Access:https://ieeexplore.ieee.org/document/8937555/

Internet

https://ieeexplore.ieee.org/document/8937555/

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