MushroomBody_Chess v2
Synaptic weights for BeatTheFly -- A Smart Fruit Fly is playing chess against you: a spiking network wired as the real Drosophila mushroom-body connectome that plays chess.
The anatomical connectome gives you wiring, not synaptic strengths. Ours are trained.
Synaptic weights trained with PHCSSM parallel-scan mode, deployment in sequential RSNN mode (PHCSSM).
made by Po-Han Chiang @ NYCU
Architecture
- Wiring: MaleCNS v1.0 mushroom body -- 4,510 neurons (4,064 Kenyon cells, 97 MBONs, 340 DANs, 2 APL, 2 DPM, 5 MB-C1) and 1,027,152 neuron-to-neuron connections. The connectivity mask is fixed to the connectome; 828,479 connections carry a nonzero weight and 0 weights lie off the connectome.
- Dale's law: one sign per presynaptic neuron from neurotransmitter annotations (excitatory 4,114, inhibitory 52, modulatory 344); 0 weights violate it.
- Inputs: each ply provides the move token (one of 1,970 UCI moves) and the board after it (789 binary features: piece per square, castling rights, en-passant file, 50-move-clock buckets, seen from the side to move). Two linear encoders with their own LayerNorm drive the Kenyon cells; the move token also drives the dopaminergic neurons.
- Neurons: leaky integrate-and-fire with per-neuron leak, threshold and reset; synaptic delay of one step.
- Fast weight: dopamine-gated associative memory on the Kenyon-cell -> MBON synapses, read back into the MBON voltages.
- Readout: linear map from the membrane voltage of all neurons to the move vocabulary.
- Deployment: sequential RSNN mode, one timestep per ply, with the neuron state and fast weight carried across the whole game.
Data sources
Data sources: human games from the Lichess open database (lichess.org, CC0); move labels from the Stockfish chess engine.
The previous version remains in this repository's history.
Evaluation
4,000 held-out Lichess games between players rated 2200+, legal moves only:
| overall | opening | early middlegame | middlegame | endgame | |
|---|---|---|---|---|---|
| agrees with Stockfish's best move | 44.7% | 92.8% | 60.2% | 38.2% | 31.4% |
Human move-match on the same games: 39.1%; on held-out Lichess blitz games (1500–1800): 36.4%.
Strength: ≈1110 Elo (95% CI ±39) vs Stockfish UCI_Elo anchors, CCRL Blitz scale, 800 games, argmax play. +139 Elo over v1 on the same openings (95% CI +75 to +211).
Files
manifest.json-- every tensor (file, dtype, shape, bytes), the model scalars and a connectome audit.info.json-- neuron metadata used by the page (cell classes, hemispheres, soma coordinates).selfcheck_<precision>.json-- reference moves and logits that the page replays when it loads.chess_uci_vocab.json-- the move vocabulary.fp16/,fp32/-- raw little-endian arrays.
Two precisions are listed in the manifest: fp16w32 (default, 49.5 MB: float16 for the
four large dense matrices, float32 for the recurrent weights and all small tensors) and
fp16 (47.8 MB, recurrent weights in float16 as well).
The recurrent weight matrix W[dst, src] is stored in CSC order by source neuron (W_colptr,
W_rowidx, W_vals): each step multiplies W by a sparse binary spike vector, so the engine visits only
the columns of the neurons that spiked. Dense matrices are stored in the orientation they are read:
enc_tok_T [vocab, H] (a move token selects one row), enc_brd_T [789, H] (sum of the active rows),
dec_w [vocab, H] and v2d_T [vocab, n_dan].
| name | file | dtype | shape |
|---|---|---|---|
enc_tok_T |
fp16/enc_tok_T.bin |
float16 | 1970x4510 |
enc_tok_b |
fp32/enc_tok_b.bin |
float32 | 4510 |
ln_tok_w |
fp32/ln_tok_w.bin |
float32 | 4510 |
ln_tok_b |
fp32/ln_tok_b.bin |
float32 | 4510 |
enc_brd_T |
fp16/enc_brd_T.bin |
float16 | 789x4510 |
enc_brd_b |
fp32/enc_brd_b.bin |
float32 | 4510 |
ln_brd_w |
fp32/ln_brd_w.bin |
float32 | 4510 |
ln_brd_b |
fp32/ln_brd_b.bin |
float32 | 4510 |
v2d_T |
fp16/v2d_T.bin |
float16 | 1970x340 |
v2d_b |
fp32/v2d_b.bin |
float32 | 340 |
dec_w |
fp16/dec_w.bin |
float16 | 1970x4510 |
dec_b |
fp32/dec_b.bin |
float32 | 1970 |
Wg |
fp32/Wg.bin |
float32 | 97x340 |
W_dan_val |
fp32/W_dan_val.bin |
float32 | 97x340 |
alpha_exc |
fp32/alpha_exc.bin |
float32 | 4510 |
alpha_inh |
fp32/alpha_inh.bin |
float32 | 4510 |
v_th |
fp32/v_th.bin |
float32 | 4510 |
reset_weight |
fp32/reset_weight.bin |
float32 | 4510 |
kc_idx |
fp32/kc_idx.bin |
int32 | 4064 |
mbon_idx |
fp32/mbon_idx.bin |
int32 | 97 |
dan_idx |
fp32/dan_idx.bin |
int32 | 340 |
W_colptr |
fp32/W_colptr.bin |
uint32 | 4511 |
W_rowidx |
fp32/W_rowidx.bin |
uint16 | 828479 |
W_vals |
fp32/W_vals.bin |
float32 | 828479 |
Numerical check: legal top-1 1968/1973 vs the fp32 reference (24 held-out games); 0 of 8,925,290 spike bits differ from the reference on the same weights.
Limitations
There is no search and no evaluation function: each move is a single timestep of the network. It is weakest in the endgame (31.4% agreement with Stockfish's best move).
License and attribution
Weights: CC-BY-NC-4.0. They are derived from the MaleCNS v1.0 connectome (Janelia FlyEM and collaborators, https://male-cns.janelia.org/, CC-BY-4.0) and trained with PHCSSM (https://arxiv.org/abs/2604.01295); please credit both.
Citation
PHCSSM: https://arxiv.org/abs/2604.01295