What does late feedback cost a market router?
research/delayed-routing
Hedge/LMSR routing with delayed feedback: regret ≤ ln N/η + ηT/8 + ηD/2 (mean delay inflates horizon by 1+4d̄), 12× regret from ignoring delay against a reactive adversary, delay-tuned rate too cautious on oblivious data, LMSR subsidy ~20× at mean delay 5.
What it found
Hedge/LMSR routing of modular experts when losses arrive after device-dependent delays: regret ≤ ln N/η + ηT/8 + ηD/2 with D the total outstanding rounds, so mean delay d̄ inflates the horizon by 1+4d̄; ignoring delay costs 12× regret against a reactive adversary at delay 100, the worst-case tuned rate is too cautious on oblivious data, an observable-count adaptive rate recovers most of it, and LMSR subsidy grows about 20× at mean delay 5. Stylised.
A figure from its own output
Paper, code and results
More in Markets as routers
- Is load balancing a congestion price?Capacity-constrained expert routing as a congestion-priced market: softmax with dual prices, verifier-computable duality-gap certificate from prices alone, sign-update balancing has a
≈2.5/√Bsampling floor plus a step-size limit cycle, closed-form two-expert price of balance, Hoeffding load audit. - Is risk tolerance the learning rate of a wealth market?Fractional-Kelly wealth markets as expert routers: risk-tolerance-weighted price,
ln(1/s)/λregret bound, growth-optimalλ*=(π−p)/(q−p), manipulation costV·χ²vs LMSRb·KL(7.5× stiffer at p=0.99), and a switching-truth trade-off whereλ≈0.1–0.2beats full Kelly 3–7×. - How should a router pick k distinct experts?Top-k MoE routing as a capped Hedge market: price
min(1, λ w_i)with exact KL projection, regret vs the best fixed k-set held underk ln(N/k)/η+ηTk/2in every run (41–58% of it), plain normalisation prices experts above 1 (282/300 rounds, loss understated 3.2×), and systematic sampling gives exactly k distinct experts with 8–14× lower variance. - How should a router treat modules that are usually asleep?A self-financed wealth ledger for specialist modules that sleep: total wealth conserved exactly, sleeping wealth frozen (one private ledger per regime), regret
≤ ln(1/π_i)/η + η·n_iin the module's *own* awake time, entry of a module with wealthεcosts incumbentsln(1/(1−ε))/η; matches the regime oracle (0.1004 vs 0.1000) where forced-to-report Hedge sits at 0.30 and fixed share is worse. - Can a module game a ledger by choosing when to sleep?When may a module choose to sleep? The ledger pays exactly leave-one-out savings
ηW_A(1−p_i)S_i; sleeping *after* seeing losses gains wealthηp_Bθ(1−θ)/2(best 1/8) and takes the market in ~130 rounds with the router's loss unchanged; committed *before* serving it is a real saving; the deterring taxηp_B/2is a fixed share that halves honest specialists in 6 rounds. - What does it cost to route between models with conditional markets, and what does a stake do to the answer?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 forτ ≤ ω), and a stake gap distorts the reported gap by a closed-form fixed point with second-order harm.
All 13 Markets as routers 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.