20 lines
904 B
Markdown
20 lines
904 B
Markdown
# Resources
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## Primary Sources
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- [SuperSpike paper (Zenke & Ganguli 2018)](https://doi.org/10.1162/neco_a_01086) — The learning rule implemented in the SNN path. Three-factor rule: eligibility trace × error signal.
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- [Tank Royale API docs](https://robocode-dev.github.io/tank-royale/) — Bot API, game physics, event model.
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- [Leaky Integrate-and-Fire model](https://neuronaldynamics.epfl.ch/online/Ch1.S3.html) — The neuron model used (EPFL textbook, free online).
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## Codebase
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- `SNNBot_garage/src/SNNBot.nim` — Main bot with SNN and reservoir paths
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- `SNNBot_garage/src/reservoir.nim` — Grid accumulator (current active path)
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- `SNNBot_garage/tests/test_bullet_economy.nim` — Automated battle test
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## To Explore
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- Hebbian learning / STDP for binary spikes
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- Hyperdimensional computing for control tasks
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- `SNNBot_garage/research/binary-snn-learning.md` — Research notes (if exists)
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