How much cheaper must an urgency cue be for the urgent before a door robot can rely on it?

What it found

society-fakeurgency gave everyone the same signalling cost and found no gain for urgent people. Here the urgent pay a share rho of what normal people pay. With 30% robots, 20% urgent people, collision cost 3 and dithering cost 1, rho = 0.5 gives urgent people +0.14 per encounter over yield-all at a normal cost of 0.6, rho = 0.25 gives +0.29 and rho = 0 gives +0.44 (perfect reading gives +0.45); at rho ≥ 0.75 there is no gain. A 10% misreading rate cuts the usable rho to 0.75 or below at the edge and 20% to 0.4. The crowd, robots included, is worse off than under yield-all in all 35 cells (+0.045 to +0.28), as it is even with perfect reading (+0.045): the fleet transfers cost from urgent people to normal people and robots. Mean field from society-fakeurgency, which was checked by simulation. Assumed, not sourced: rho and the signal costs (swept), round-figure door costs, logit sharpness, no robot learning, random pairing.

A figure from its own output

Paper, code and results

• README and method
• Experiments and results
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More in Robot societies among people

• At what collision cost does a door stop tempting robots to go first?At what collision cost does a door stop tempting robots to go first? With 30% robots and dithering cost 1, always-yielding robots are individually stable only above a collision cost of 2.80 (waiting cost 1); below it a single robot gains by going though yielding is best for the crowd. The threshold rises with dithering cost and robot share.
• When robots always yield at a door, do people learn to walk through first, and who pays?When robots always yield at a door, do people learn to walk through first, and who pays? Always-yielding robots raise the share of people who go from 0.388 to 0.595 at 50% robots and cut the crowd's cost (1.064 to 0.968); always-going robots raise it to 1.373. Mean field and simulation agree within 0.003.
• Can a few queue-enforcing robots hold a queueing norm against line-cutting robots?How many enforcer robots hold a queue against line-cutting robots? About 5% of the crowd holds the norm against 30% cutters (memory 9, 10 people in view of each cut, stop chance 0.5), simulation agrees. Stylised: view size and stop chance are swept, not sourced.
• Do stubborn walkers who convert after meeting robots let a smaller robot minority tip a crowd's walking side?Do stubborn walkers who convert after meeting robots let a smaller robot minority tip a crowd's walking side? At 24% robots every crowd tips for k = 30 meetings (median round 171) though the fixed block stops it; at 16-20% none tip.
• Can a robot that yields to people in a hurry survive people faking a hurry?Can a robot that yields to people in a hurry survive people faking a hurry? With 30% robots, no signal cost on a 0 to 1.2 grid lets a signal-reading fleet beat yield-all for the crowd, and urgent people keep about 6% of the gain they get from perfect reading.
• Does the rule that robot blocks must be narrower than the neighbourhood carry over from a ring to a 2D grid?On a 16x16 torus (memory 9), robot patches up to about 2k+1 sites wide tip every crowd at robot share 0.25 and wider ones tip few or none; one 8x8 patch of all the robots tips none at any neighbourhood radius up to 5.

All 31 Robot societies among people projects →

Other research topics

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.