What does it cost to route between models with conditional markets, and what does a stake do to the answer?
research/decision-markets
Conditional markets that route between models: inverse-propensity Brier is proper even when the router reads the report, exploration costs exactly 1+(K−1)e^{ω²/2τ²} in payment variance (probit: infinite for τ ≤ ω), and a stake gap distorts the reported gap by a closed-form fixed point with second-order harm.
What it found
Markets that forecast each model’s loss if chosen only ever see the chosen arm. An inverse-propensity Brier payment is exactly proper even when the router reads the report (without the weight a trader shades its forecast, or hides), and its price is exact: E[1/π] = 1+(K−1)eω2/2τ2, so payment variance blows up as the router cools (a probit router has infinite variance for τ ≤ ω; Monte Carlo at τ=0.3 sees 29 against the exact 195). Exploration regret is at most 0.2785τ. Equal owner stakes cancel in the decision, a stake gap shifts the reported gap by a closed-form fixed point, and the loss it causes is second order, ∝(ΔB/k)2. Gaussian, one-shot, stylised.
A figure from its own output
Paper, code and results
More in Markets as routers
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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.