A Hybrid Multi-Task Learning Approach for Optimizing Deep Reinforcement Learning Agents

A Hybrid Multi-Task Learning Approach for Optimizing Deep Reinforcement Learning Agents

Driven by recent technological advancements within the field of artificial intelligence (AI), deep learning (DL) has been emerged as a promising representation learning technique across different machine learning (ML) classes, especially within the reinforcement learning (RL) arena. This new directi...

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Bibliographic Details
Main Authors: Nelson Vithayathil Varghese, Qusay H. Mahmoud
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Machine learning
deep reinforcement learning
neural networks
transfer learning
actor-critic
multi-task worker
Online Access:https://ieeexplore.ieee.org/document/9376851/

Internet

https://ieeexplore.ieee.org/document/9376851/

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