[HN Gopher] Evolving Reinforcement Learning Algorithms
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       Evolving Reinforcement Learning Algorithms
        
       Author : graderjs
       Score  : 97 points
       Date   : 2021-04-25 06:11 UTC (16 hours ago)
        
 (HTM) web link (ai.googleblog.com)
 (TXT) w3m dump (ai.googleblog.com)
        
       | neatze wrote:
       | I fail to understand how such work should not mention neuro
       | evolutionary argument typologies (NEAT).
       | 
       | Does there's work substantially different then NEAT ?
       | 
       | How does there's work compares in performance to NEAT ?
        
         | nuclearnice1 wrote:
         | Great questions!
         | 
         | The blog points to their paper. Kenneth Stanley gets a mention
         | in the first paragraph on related work.
         | 
         | As far as difference, there are many. A major one is NEAT uses
         | a direct encoding of the connections whereas this paper
         | introduces this language describing the RL algorithm. Evolution
         | is then conducted on trees where nodes are operators in that
         | language.
         | 
         | Performance comparison is complicated. A major issue is this
         | paper finds graphs for doing RL. So it re-discovers TD or
         | evolves an improved version of DQN. Whereas NEAT seems to
         | evolve networks suited to specific tasks like pole balancing.
        
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       (page generated 2021-04-25 23:02 UTC)