LLM Agents Play Pokemon Showdown (olivergrabner.com)

15 points by grabnero 2 hours ago

10 comments:

by minimaxir 40 minutes ago

As a tangent, there has recently been drama with AI and Pokemon Showdown because someone trained a bot (using standard reinforcement learning + a rewrite of the Pokemon battle engine to Rust for max self-play parallelism) that is apparently good enough to get to the top of the leaderboard.

by grabnero 36 minutes ago

Yeah I saw that too which was partly the inspo for this experiment. I feel like its kind of getting to a place like in chess where AI is getting better and while theres alot of drama right now, I feel like it'll be something like stockfish in the future

by jfreds 32 minutes ago

Did you try out different reasoning levels? Wondering if messaging is basically a proxy for additional reasoning

by pgn an hour ago

what was the selection for the teams? random per round? how does it play against people in ladder?

by grabnero 41 minutes ago

Yeah! So I did teams from a fixed, random seeded pool and then would rerun it with the switched teams. It also doesn't play against ladder yet but I played against it and it's not horrible. It plays better than an amateur but I was able to beat it a good amount

by doctorpangloss an hour ago

Pokémon Showdown isn't a game so much as it is competitive Wiki reading.

by grabnero an hour ago

Not going to lie I agree lol but still interesting to see

by deadbabe 2 hours ago

Jev will give better results on this kind of thing.

by nico an hour ago

For sure are many better models for this use case[0]

At the same time, it’s interesting seeing how generally capable language models/LLMs/agents/harnesses are getting

We’ll probably see a lot more experiments and benchmarks like these in the near future

0: simple classifiers can play quite a few game, including Doom https://playground.jeffyclassify.com/#doom

by grabnero an hour ago

Yeah Jev can play it but Jev cant communicate with its teammate in the 2v2 + it cant reason and is just a decision model

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