Implementing Empathic Intelligence: The Murène Engine Code Walkthrough

[louisLeprieur]

Code Architecture :

class MureneSystem:

def __init__(self):
self.agents = [] # Political and civilian entities
self.W = [] # Empathic connection weights
self.D = 5.0 # Global disorder
self.Dm = 1000.0 # Moral debt

Key Algorithmic Insights

1. Biological Plausibility:

   • Stress effects on empathy (cortisol → reduced γ)

   • Emotional contagion (weight updates)

   • Stochastic variability (Beta-distributed η)

2. Theory of Mind Integration:

   • Each agent models others’ emotional states (P_j)

   • Enables predictive empathy and proactive conflict resolution

3. Safe Optimization:

   • Political entities can bear negative utility, civilians cannot

   • No genocide constraint hardcoded: if any(a.utility < 0 and not a.is_political): return 0.0

Empirical Results :

All simulations show consistent patterns:

• Rapid initial B improvement (0 → 7+ in ~500 steps)

• Stable oscillation around ethical optima

• Convergence to B > 8.0 for validated solutions

Open Questions for Technical Readers :

1. How sensitive are results to parameter calibration?

2. Could this framework be integrated with existing RL systems?

3. What’s the computational complexity for large-scale conflicts?

4. How do we prevent “ethics hacking” of the beauty metric?