Network Economy Testbed Interpretation

Verdict

The learned three-layer economy is close to a clearing/Nash-type operating point. Tail clearing residual is 0.0022; VI residual proxy is 0.0107. Mean surplus is 15.3230; route entropy is 0.9882. Prometheus built 24 local PSR contexts from 6000 role reports.

Equilibrium Readout

A solved run has low market-clearing residual and low role-level one-step incentive gaps, a finite diagnostic proxy for the variational-inequality condition.

  • `network_clearing_like`: `True`
  • `tail_mean_market_residual`: `0.0022`
  • `tail_max_market_residual`: `0.0022`
  • `vi_residual_proxy`: `0.0107`
  • `tail_mean_total_surplus`: `15.323`
  • `tail_mean_unmet_demand`: `0.004`
  • `tail_mean_idle_supply`: `0.003`
  • `tail_mean_idle_transport`: `0.039`
  • `tail_mean_route_entropy`: `0.9882`
  • `tail_bottleneck_entropy`: `0.0`
  • `low_flow_warning`: `False`
  • bottlenecks: `{'producer': 1500}`
  • top routes: `{'P1>T1>C1': 750, 'P2>T1>C1': 250, 'P1>T2>C2': 250, 'P1>T1>C2': 250}`

    • Role Strategies

    Consumer

  • agents: `['C1', 'C2']`
  • dominant tail action: `demand:high`
  • dominant tail route: `P1>T1>C1`
  • mean tail quantity: `8.775`
  • mean tail price: `3.188`
  • mean tail freight rate: `0.0`
  • mean tail investment: `0.0`
  • mean tail payoff: `7.663`
  • one-step incentive gap: `0.0107`
  • planner counts: `{'consumer_psr_route_utility_response': 2000}`

    • Producer

  • agents: `['P1', 'P2']`
  • dominant tail action: `offer:balanced|price:balanced`
  • dominant tail route: `P1>T1>C1`
  • mean tail quantity: `8.7745`
  • mean tail price: `2.184`
  • mean tail freight rate: `0.0`
  • mean tail investment: `0.0`
  • mean tail payoff: `8.1985`
  • one-step incentive gap: `0.0076`
  • planner counts: `{'producer_psr_price_quantity_response': 2000}`

    • Transport

  • agents: `['T1', 'T2']`
  • dominant tail action: `carry:balanced|rate:high|invest:low`
  • dominant tail route: `P1>T1>C1`
  • mean tail quantity: `8.7925`
  • mean tail price: `0.0`
  • mean tail freight rate: `0.906`
  • mean tail investment: `0.006`
  • mean tail payoff: `4.1745`
  • one-step incentive gap: `0.0056`
  • planner counts: `{'transport_psr_capacity_investment_response': 2000}`

    • UDL Kan Loop

  • left Kan extension: `realized_network_rollout`
  • rollout stream: `local signal -> role action -> market clearing -> payoff`
  • right Kan extension: `strategy_from_role_local_psr`
  • strategy objects: `{'consumer_psr_route_utility_response': 2000, 'producer_psr_price_quantity_response': 2000, 'transport_psr_capacity_investment_response': 2000}`
  • readout: The left Kan side builds the network economy from realized token flows; the right Kan side queries role-local PSRs to adjust supply, capacity, and demand.

    • Prometheus Artifacts

  • trace: `/Users/sridharmahadevan/Downloads/mac-cech_homology_GT/Prometheus_v1/runs/prometheus_gui/run-0003-run-the-network-economy-token-flow-demo-0b425c4cab/network_economy_demo/network_economy_agent_reports.jsonl`
  • world model: `/Users/sridharmahadevan/Downloads/mac-cech_homology_GT/Prometheus_v1/runs/prometheus_gui/run-0003-run-the-network-economy-token-flow-demo-0b425c4cab/network_economy_demo/prometheus_world_model.json`
  • PSR bundle: `/Users/sridharmahadevan/Downloads/mac-cech_homology_GT/Prometheus_v1/runs/prometheus_gui/run-0003-run-the-network-economy-token-flow-demo-0b425c4cab/network_economy_demo/prometheus_psr_bundle.html`

    • Prometheus parses each role report into signal, local state, action, clearing, and payoff events. Those events induce role-local PSRs, agent-local PSRs, restriction diagnostics, and gluing diagnostics.