Does a measured walking-side preference pin down how many robots tip a crowd's passing side?

What it found

society-blocs swept the share of always-left people by hand. Here the share is fitted instead: the status-quo crowd must show the left share Moussaïd et al. (2009, Proc. R. Soc. B 276) measured when two walkers meet head on, which I read from their Fig. 4 bars as 0.175 (static obstacle: 0.40; the paper prints no numbers, reading error about 0.01). Always-left share and error rate trade off along the fit (at memory 9: 0.155 at ε = 0.02 down to 0.019 at 0.30), yet the tipping robot share barely moves along it: 0.075 to 0.096, against 0.217 with no bias. Memory length and a stubborn-right bloc move it more (memory 5: 0.033–0.053; 17: 0.133–0.149; with 30% always-right, 0.135–0.151 at memory 9). Simulation (200 people, 12 seeds) reproduces the left share (0.170–0.171) and tips 0 of 12 crowds 0.04 below and 12 of 12 0.04 above the mean-field value. Limits: one binary game in a well-mixed crowd, two walkers in a corridor are not a crowd, the bar heights are read from a figure, and the measured pairs may be partly stubborn and partly noisy in ways this cannot tell apart.

A figure from its own output

Paper, code and results

• README and method
• White paper
• Experiments and results
• Code
• Tests

More in Robot societies among people

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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.