import numpy as np

def run_simulation(agents, steps, noise, coupling):
    n = len(agents)
    history = []
    state = agents.copy()

    for _ in range(steps):
        new_state = state.copy()

        for i in range(n):
            interaction = np.mean(state) - state[i]
            new_state[i] += coupling * interaction

        new_state += np.random.normal(0, noise, size=n)
        new_state = np.clip(new_state, 0, 1)

        history.append(new_state.copy())
        state = new_state

    return history