Validation Suite

# BTUT Validation - Nash-Gap Convergence
import numpy as np

NUM_AGENTS = 1000
KERNEL_BANDWIDTH = 0.1

def gaussian_kernel(x, y, sigma=KERNEL_BANDWIDTH):
    return np.exp(-np.linalg.norm(x - y)**2 / (2 * sigma**2))

def compute_nash_gap(agents):
    mean_strategy = np.mean([a.u for a in agents], axis=0)
    return np.mean([np.linalg.norm(a.u - mean_strategy)**2 for a in agents])

# Run simulation
for iteration in range(50):
    agents = fokker_planck_step(agents)
    gap = compute_nash_gap(agents)
    if gap < 0.001:
        print(f"Converged at iteration {iteration + 1}")
        break