About · Move 37 → Move42

The next move is an algorithm.

Move42 is a VEOX research project. InnovationZero is the reported method.

Why Move42

A requirement is a board. The contract defines legal play. The referee decides what worked.

state → legal action → external consequence → preserved experience.

The proposed output changes from an answer or score to an independently runnable method. The learning target is the distribution of later executable proposals across requirements.

AlphaGo’s Move 37 became shorthand for a machine finding a powerful move inside a fixed game. Move42 asks whether the action itself can become a complete executable algorithm for a new requirement.

Where search occurs

Where search occurs

Search now. Learn for later. Or combine both.

Current requirement

AutoResearch improves through a proposal–execution–inspection–retry loop on the current requirement.

Across requirements

Move42 aims to improve the proposal distribution across requirements, so the first executable move itself becomes learnable.

Hybrids remain possible; the distinction is where search occurs and what persists between tasks.

Evidence boundary. The current record does not measure superiority over research agents, task-time speedup, or an admitted prospective strict first move.

The game we are trying to build

  1. 01

    Board

    The requirement plus every permitted input, state transition, and resource boundary.

    Encode the requirement and permitted state before any proposal is made.
  2. 02

    Move

    One complete executable algorithm whose outputs can be independently reproduced.

    Define the runnable artifact, interface, and terminal outputs that count as a move.
  3. 03

    Rules

    The legality contract that rejects shortcuts, leakage, hidden state, and invalid resources.

    Close shortcut and leakage paths before play, then make every violation an explicit failure.
  4. 04

    Referee

    An external consequence-based evaluator that executes the move and records success or a named failure.

    Build the referee outside model self-assessment and bind its identity to every outcome.
  5. 05

    Memory

    Canonical success and failure receipts that can supervise later proposals across requirements.

    Preserve receipts, train later proposals, and separately freeze a true one-proposal prospective evaluation.

What does this mean?

Vision · Compiler game

Board
A source program, target semantics, architecture, and optimization contract.
Move
A complete transformation or optimization algorithm that produces executable output.
Referee
Correctness suites, resource limits, and consequence-based performance measurements.

A design horizon, not a finding of the current regression study.

Vision · Control game

Board
A control requirement, observable plant state, hard constraints, and permitted actuators.
Move
A complete control algorithm that can be executed against the declared interface.
Referee
Constraint violations, stability, resource use, and measured physical consequence.

A design horizon, not evidence of autonomous control performance.

Vision · Experimental game

Board
An apparatus, measurement protocol, budget, safety envelope, and experimental objective.
Move
A complete executable experiment schedule and analysis method.
Referee
Predeclared measurements, explicit failure outcomes, and independently preserved receipts.

A design horizon, not an experimental result reported here.

Vision · Scientific-design game

Board
A scientific question, admissible evidence, interventions, and falsification criteria.
Move
A complete executable design for collecting and analyzing the next evidence.
Referee
Preregistered consequence tests that can reject as well as support the proposed method.

A design horizon, not a claim of causal or scientific discovery.

What we publish

The site contains the algorithm-first flagship, a purpose-designed editorial brief, the active immutable v1 paper, the complete seven-act mirror, the full recorded-move atlas, separated evidence classes, archive-bound provenance, and explicit limitations. There is no signup, analytics, contact submission, public mutation endpoint, or hidden application backend.

What remains unproved

The historical record does not establish prospective one-proposal performance, expected future win rate, universal superiority, or safe autonomous use. Those boundaries are part of the thesis, not footnotes to it.