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Show HN: A competition for small neural networks that play strategy games
- codetiger 12d ago15yrs back I participated in "Google Ants AI Challenge 2011", an ai programming competition, hosted by the University of Waterloo, and I ranked #127 (#1 in my country). The competition gave me a huge learning oppurtunity where developers across the world came to a forum and discussed various techniques. Now, I've built a similar platform to bring back the fun of building a small neural network that can play the game well. Neural Network optimization seems to be much more fun. Plz share your feedback to improve the platform and add more games.
- atmanactive 12d agoI remember a game on Steam called Tiny Brains, great couch co-op.
- AnotherGoodName 11d agoNice. I was 72nd. Working in AI research today and still making ai for games as a hobby (tfmbot.com is an ai i’m working on for my favourite board game terraforming mars).
- codetiger 11d agoThanks for sharing. I remember #1 xathis had a score, big leap ahead of others. The difference in techniques in top 100 was almost the same.
- Muthaalagan 11d agoFrom competing with the world to building a place for the world to compete—what a full-circle moment. Love the challenge: how much strategy can a tiny neural network learn? Excited to see what people build.
- nickledave 11d agoNice work, the new site looks great. Can you give more background on the Ants game? I didn't find it on the current site or the older one. Was the game inspired by anything like agent-based simulations? I'm not super interested in what the tech industry is calling "agentic" AI, but I am interested in collective intelligence, see David Ha's work in this area: - https://journals.sagepub.com/doi/full/10.1177/26339137221114874 https://journals.sagepub.com/doi/full/10.1177/26339137221114... - https://neurips.cc/virtual/2024/105817 https://neurips.cc/virtual/2024/105817 Would be cool if each ant itself could be an agent
- codetiger 11d agoUnfortunately the competition site is mostly down and couldn't find much about the old competition other than the participants blog articles. Do a search on "Google Ants AI Challenge - post mortem", and you get a lot of articles around the game. Thanks for sharing the research. I tried implementing a per Ant decision making model, but gave up as the training time was much longer compared to the current baseline. I think I should rethink the idea.
- adityamishra241 12d agoThis looks fun. How small are the networks you're aiming for?
- lostdog 11d agoCool idea! It would help to delete all the text on the page, and write it without AI. For example, "model and manifest bytes together pick the class; every version also plays on Open"
- codetiger 11d agoThanks for the feedback. I’ll take that as top priority.
- deleted 11d ago[deleted]
- lokar 11d agoSee also: https://en.wikipedia.org/wiki/Core_War https://en.wikipedia.org/wiki/Core_War
- willmarch 11d agoPretty neat! I'm considering entering some models. How long will you be running these competitions?
- Qworg 11d agoReminds me of MechMania at UIUC - exciting!
- adityamishra241 11d agoThis looks fun. How do you evaluate the networks — is it purely based on game performance, or are there other metrics like size and inference speed too?
- cookiengineer 11d agoOMG! Just yesterday I published my reworked GoNEAT library that implements HyperNEAT combined with phased search and backpropagation [1]. But it's kind of impossible to enter for me because of the hard pytorch requirements :( would love to see the project as a gym, so that you can run your own ANN design algorithm. I get that most data science students still use python, but the evolutionary world is kinda in C++ and other native languages. Anyways, great project nonetheless. [1] https://github.com/cookiengineer/goneat https://github.com/cookiengineer/goneat
- codetiger 11d agoWhere do you see a hard requirement? I have added support for ONNX model upload for now and would love to extend support for other formats. How you build the model is totally upto you. I don’t check anything other than format and inference time and model size.
- codetiger 11d agoSaw your repo and understood you question better. The requirement are now limiting Neural Networks only, not a direct algorithm implementation
- DylanMerigaud 11d agoGreat idea to focus on small, efficient neural networks.
- awfm9 11d agoMan, I remember doing this is 2011 as well. Everything some kind of hand-coded strategy. I enjoyed it a lot.
- Muthaalagan 11d agoInteresting—how small can a neural network get and still make good strategic decisions? Curious whether these models can adapt to unfamiliar opponents.
- vova_hn2 11d ago> Your class is measured, not chosen > model and manifest bytes together pick the class What? How hard is it to write something like "your weight class is determined by the total size of the model and manifest" (if I understood it correctly). Current version both sounds very AI-sloppy and is ambiguous. The doc page [0] is even more painful to read. [0] https://tinybrains.dev/docs/models/weight-classes.html https://tinybrains.dev/docs/models/weight-classes.html
- FrustratedMonky 11d agoNot all sloppy writing is AI. Quite a few humans also write ambiguously.
- euroderf 11d agoLet's play real stuff. "Playing Hex and Counter Wargames using Reinforcement Learning and Recurrent Neural Networks" https://arxiv.org/pdf/2502.13918 https://arxiv.org/pdf/2502.13918
- TeMPOraL 11d agoIs "Hex" real stuff? I know that from university AI courses, from before current ML phase. I thought this was a toy game invented specifically to be nice for AI exercises - bounded, easy to follow, moderate branching factor, and designed to make ties impossible.
- WanderZil 11d agoThis reminds me of John Conway's Game of Life. I wonder what surprises we could get by combining Game of Life with neural networks
- alex7o 11d agoIt would be cool for sb to try jev on it :P although this is not text input at all