[HN Gopher] Neural Chess
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       Neural Chess
        
       Author : fagnerbrack
       Score  : 22 points
       Date   : 2024-03-07 18:03 UTC (4 hours ago)
        
 (HTM) web link (pvdz.ee)
 (TXT) w3m dump (pvdz.ee)
        
       | Imnimo wrote:
       | Am I reading right that the network here is an MLP with a single
       | hidden layer of 50 neurons? It's a fun project, but I think the
       | author would have benefitted from spending more time on finding a
       | reasonable network architecture instead of jumping into the
       | (admittedly alluring) quagmire of RL.
        
       | seunosewa wrote:
       | Should he have introduced some randomization to prevent the
       | repetition of moves?
        
       | roenxi wrote:
       | The article's claim that we can see the "video here" is false -
       | the link is broken. The video is here:
       | https://www.youtube.com/watch?v=DcYLT37ImBY. It is a really
       | interesting showcase and something is happening there that the
       | writer at pvdz.ee didn't seem to find as interesting as I do.
       | 
       | There is a concept that I bumped into of "Novelty Search" in the
       | genetic algorithm space. Rather than trying to guess what
       | behaviour is "good" and reward it, instead reward some novelty
       | heuristic. Agents explore the space more thoroughly. The video is
       | a really quite a good showcase of the technique - he only encodes
       | hints on how to play _after_ a pure novelty based approach is
       | shown to fail.
       | 
       | pvdz.ee seems to be trying to encode his game knowledge into the
       | reward function early and seemed unsatisfied in the results based
       | on his discussion.
       | 
       | If I had a Nvidia graphics card instead of an AMD one, an
       | experiment I'd have run a few years ago was a Go AI that tried to
       | find a novel move heuristic to see if that sped up training. But
       | that was a few years ago, I was defeated by the poor compute
       | driver situation and haven't felt the urge since.
        
       | gwern wrote:
       | > Actually, my first thought was to just feed these pgn strings
       | to a network and create an LLM-esque sort of network. But I
       | wasn't convinced that I was going to get that anywhere within
       | reasonable time.
       | 
       | A number of people have done this in various forms (including,
       | advertisement, Shawn Presser & myself way back in January 2020
       | with GPT-2: https://slatestarcodex.com/2020/01/06/a-very-
       | unlikely-chess-... ); eg https://github.com/ricsonc/transformers-
       | play-chess/blob/mast... It's actually extremely easy, you could
       | get started within hours at this point, with all the
       | infrastructure for finetuning LLMs these days.
       | 
       | Beyond the hobbyist/research level, people have noted that
       | ChatGPT-3/4 are pretty good at chess, and the reason for that
       | seems to be that they dumped an ELO-filtered PGN dataset into the
       | training corpus (for unclear reasons, given how much data that
       | would be but also how useless that would seem to be).
        
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