Multi-Alpha Soft Actor-Critic: Overcoming Stochastic Biases in Maximum Entropy Reinforcement Learning-Reference-Cited by-同舟云学术

Multi-Alpha Soft Actor-Critic: Overcoming Stochastic Biases in Maximum Entropy Reinforcement Learning

Published:2023-05-29 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Robotics and Automation (ICRA)
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Author:

Igoe Conor¹,Pande Swapnil²,Venkatraman Siddarth²,Schneider Jeff²

Affiliation:

1. School of Computer Science, Carnegie Mellon University,Machine Learning Department,Pittsburgh,PA,United States,15213

2. Robotics Institute, School of Computer Science, Carnegie Mellon University,Pittsburgh,PA,United States,15213

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10160211/10160212/10161395.pdf?arnumber=10161395

Reference29 articles.

1. Reinforcement learning with deep energy-based policies;haarnoja;International Conference on Machine Learning,2017

2. panda-gym: Open-Source Goal-Conditioned Environments for Robotic Learning;gallouédec;4th Robot Learning Workshop Self-Supervised and Lifelong Learning at NeurIPS,0

3. CARLA: An open urban driving simulator;dosovitskiy;Proceedings of the 1st Annual Conference on Robot Learning,2017

4. Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor;haarnoja;International Conference on Machine Learning,2018

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