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Self-replicating manufacturing

Which machine should a seed shop add next, and does a greedy rule find it?

research/selfrep-nextmachine

Which machine a printer-only seed shop should add next under a budget: greedy closure-per-price vs exhaustive search; same choice on the real 3-machine instance, optimal in 72–94% of 500 synthetic instances. Machine prices assumed. Stylised.

6 tests

What it found

Builds on the selfrep-closure part model. Choosing among a CNC router, laser cutter and casting setup under a budget, a greedy closure-per-price rule matches exhaustive search at every tested budget on the real three-machine instance (router first, then casting only if brass bushings replace LM8UU). On 500 random synthetic instances greedy is optimal in 72–94% of cases and loses up to about 38% of the closure gain in the worst case. Stylised: machine prices, masses and costs are assumed placeholders, machines have no bills of materials of their own, and the synthetic instances are random.

A figure from its own output

Figure produced by research/selfrep-nextmachine: closure
selfrep-nextmachine/experiments/closure.svg, written by the project's own experiment code.

Paper, code and results

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Proper scoring & elicitation28Effort & peer prediction9Verification games & slashing19Detection & tolerances14Markets as routers13Prediction-market design9Paying contributors8Decentralised training systems23Digital twins & sim-to-real164LLM chip design loops40Robot manufacturing loops53Ambient AI assistant46Self-replicating manufacturing34Simulation-first design64Engineered clothing45Task-specific AI accelerators40Algorithmic chip-design loops42Open-source purpose-built robots44The software-engineering loop43Adversarial human imitation41Open-source residential construction41Autonomous multi-angle capture34Sensing, imaging and 3D31Energy supply and dense energy storage39Robot societies among people31Agentic co-design of low-cost robots27Laundry-hanging robots25Machine learning on qualitative data23Robots on the building site27Civilizations & group psychology1History & human sciences1

Produced with AI assistance (Claude). Results are from the code in this repository and are simulated or stylised unless the abstract says otherwise; nothing here implies affiliation with or endorsement by any lab, researcher or company cited. MIT licensed.