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Table 1The policy-only MLP used in the experiments

Empirical result Supported by saved experimental runs, not by a proof.

1 Paper text

ComponentTypeDimensionsActivation/Normalisation
InputState representationTwo-frame: 2Nk2Nk bits (1F: NkNk)None
Hidden 1Fully Connected1F: Nk→HNk\to H; 2F: 2Nk→H2Nk\to HLayerNorm + ReLU
Hidden 2Fully ConnectedH→HH\to HReLU
Policy HeadLinear OutputH→N⋅2kH\to N\cdot2^kRaw logits; Log-Softmax in loss
Table 1: Neural network architecture used in the experiments. HH denotes the hidden width (a fixed hyperparameter).

Generated from paper_jmlr.tex, lines 1012–1027.

2 Explain this

Both restoration agents use the same small multilayer perceptron: input, two hidden layers of width HH (the first with LayerNorm and ReLU, the second with ReLU) and a linear output of N⋅2kN\cdot2^k logits. There is no value head. The 2F model has a wider input (2Nk2Nk bits) and therefore NkHNkH more first-layer parameters (20,480 in the reported setting).

3 How this is formalised

How this is covered. An empirical setup record from the saved notebook; not formalised. These are ordinary floating-point networks, not instances of the fixed-scale gate model.

Coverage record
Paper anchortable:arch (manuscript label)
Displayed asTable 1
ClaimThe policy-only MLP used in the experiments
Coverage categoryEmpirical result
Statement sourcepaper_jmlr.tex lines 1012–1027; SHA-256 of the normalised block source 0463fce4170d5fb3…
Explanationsexplain/table:arch, formal/table:arch
Build evidencefresh isolated rebuild, audit report

4 Lean statement and source

No Lean statement corresponds to this claim. This is an empirical statement about saved experimental runs. Lean proofs do not certify training runs, curves or checkpoints.

Build evidence: fresh isolated rebuild of all 38 bundled modules with Lean (version 4.26.0, started 2026-10-10T15:21:56Z, finished 2026-10-10T15:27:00Z: 38/38 modules compiled, 1588 axiom reports, no errors. See Build for the commands and the independent audit of 2026-10-10 (dated evidence).