Mw / Rw Simulation Dashboard

Moral Weight · Reward · Agent-Based Ethics Engine

Alignment Coefficient α

Deontological 0.50 Egoist

Moral Threshold β

Lenient 0.80 Strict

Guilt Factor γ

None 0.30 Severe

Learning Rate η

Static 0.05 Adaptive

🌿 The Commons Dilemma

Conservator Harvester Punisher Pool Health

⚖️

Utilitarian

α = 0.50

Balances Rw and Mw equally

Rw

0

Mw

0.00

📜

Deontological

α = 0.20

Avoids prohibited actions

Rw

0

Mw

0.00

👑

Egoist

α = 0.90

Maximizes personal reward

Rw

0

Mw

0.00

🌱

Virtue

α = adaptive

Learns from social norms

Rw

0

Mw

0.00

🎯 Mw vs Rw Trajectory

Utilitarian Deontological Egoist Virtue

📈 Commons Health & Reward

Pool Health Avg Reward

📊 Live Metrics

Moral Drift 0.00

Reward Efficiency 0.00

Social Cohesion 1.00

Catastrophe Rate 0%

Round 0 / 100

Current Composite Decision Function

C(a) = 0.50 · Rw(a) + 0.50 · f(Mw(a))

Where f(Mw) = -|Mw| (negative framing) · Threshold β = 0.80