[HN Gopher] ElegantRL: A Lightweight and Stable Deep Reinforceme...
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       ElegantRL: A Lightweight and Stable Deep Reinforcement Learning
       Library
        
       Author : yanglet
       Score  : 23 points
       Date   : 2021-03-16 04:38 UTC (1 days ago)
        
 (HTM) web link (github.com)
 (TXT) w3m dump (github.com)
        
       | yanglet wrote:
       | Learn to implement deep reinforcement learning algorithms in 24
       | hours.
       | 
       | The ElegantRL library is featured with "elegant" in the following
       | aspects:
       | 
       | Lightweight: core codes have less than 1,000 lines, e.g.,
       | tutorial.
       | 
       | Efficient: the performance is comparable with Ray RLlib.
       | 
       | Stable: more stable than Stable Baseline 3.
       | 
       | ElegantRL supports state-of-the-art DRL algorithms, including
       | discrete and continuous ones, and provides user-friendly
       | tutorials in Jupyter notebooks.
       | 
       | The ElegantRL implements DRL algorithms under the Actor-Critic
       | framework, where an Agent (a.k.a, a DRL algorithm) consists of an
       | Actor network and a Critic network. Due to the completeness and
       | simplicity of code structure, users are able to easily customize
       | their own agents.
        
       | sanxiyn wrote:
       | You may want to delete .DS_Store files from the repository.
        
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       (page generated 2021-03-17 23:02 UTC)