模拟果蝇大脑学会赛车：用 Elo、赛季和家族血统打造 24/7 赛车联赛
A simulated fruit fly brain learns to drive. I turned the training into a 24/7 racing league with Elo, seasons and family dynasties [P]
有人用约 2400 个神经元的果蝇大脑模型在直线竞速模拟器中训练驾驶，并做成带 Elo 评级和赛季的 24/7 直播联赛。每个"车手"已累计训练超 1000 万回合，表现最好的个体会产生继承权重的"后代"，形成家族血统。目前进行到第 11 赛季第 86 站，干燥赛道纪录为 10.06 秒，冠军在 5 个场景总成绩 56.31 秒。
For the past 4 weeks I’ve been training models of the Drosophila brain to control a car in a drag racing simulator. To make the training watchable, I turned it into a racing league and stream it live on Twitch.
How it works
- Each “pilot” is a fly brain model of ~2,400 neurons [based on: FlyWire connectome / own architecture / spiking network?]
- Training: [RL algorithm / evolutionary strategy / plasticity rule], 10000000+ episodes so far
- The best pilots produce “offspring”: the next generation inherits their weights, so the league has dynasties (gen 2, child of the season champion, etc.)
- Every Grand Prix is a set of races under different conditions (engine, grip, dry/wet). A fly is “verified” only if it finishes all scenarios cleanly
- Skill is measured with an Elo rating, like in chess
Current state (Season 11, GP 86): the dry-strip record is 10.06 s; the champion has 56.31 s total across 5 scenarios. Last GP was won by a second-generation fly, 0.02 s ahead of its rival.
What surprised me: [1–2 real observations, e.g. “flies discovered launch control on their own”, “descendants overtook the parent in 300 episodes”, “one fly learned to exploit…”]
🔴 Live: twitch.tv/nekrampos
[💻 Code: https://github.com/boeing240/flypilot\]
Happy to answer questions about the model, the training setup and the visualization. Ideas for new race scenarios are welcome too.
submitted by /u/Pepegg2
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来源：r/MachineLearning · reddit.com