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by ide0666
71 days ago
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We're exploring related ideas in embodied AI rather than LLM agents. MH-FLOCKE uses Izhikevich spiking neurons with R-STDP to control quadruped locomotion — the memory is in the synaptic weights, not in a vector store. The brain persists across sessions: stop the robot, restart it, synaptic weights reload and it continues from where it left off. Decay happens naturally through R-STDP — synapses that don't contribute to reward weaken over time. No explicit forgetting mechanism needed. Currently running on a Unitree Go2 (MuJoCo) and a 100€ Freenove robot dog (Raspberry Pi 4, real hardware). Same architecture, different bodies. github.com/MarcHesse/mhflocke |
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