Crosswalk Problem

Mechanism design — the canonical GDS example from BlockScience.

A pedestrian decides whether to cross a one-way street while traffic evolves as a discrete Markov chain. A governance body chooses crosswalk placement to minimize accident probability.

GDS Decomposition

X = traffic_state ∈ {-1, 0, +1}
U = (luck, crossing_position)
g = pedestrian_decision
d = safety_check
f = traffic_transition
Θ = {crosswalk_location}

Composition

observe >> decide >> check >> transition

flowchart LR
    Observe([Observe Traffic]) --> Decide[Pedestrian Decision]
    Decide --> Check[Safety Check]
    Check --> Transition[[Traffic Transition]]

What You'll Learn

• Discrete Markov state transitions as GDS
• Mechanism design: governance parameter (crosswalk location) constraining agent behavior
• ControlAction for admissibility enforcement (safety check)
• Complete 4-role taxonomy in a minimal model
• Design parameter Θ as a governance lever

Files

• model.py
• test_model.py
• VIEWS.md
• README.md