def METHOD_NAME(x_init, _A, _B):
    lti = pp.module.LTI(exp['A'], exp['B'], C, D, c1, c2)
    stepper_exp = pp.utils.ReduceToBason(steps=1, verbose=False)
    mpc_exp = pp.module.MPC(lti, exp['Q'], exp['p'], T, stepper=stepper_exp) # expert
    x_true, u_true, cost_true = mpc_exp.forward(dt, x_init)
    lti_ = pp.module.LTI(_A, _B, C, D, c1, c2)
    stepper_agt = pp.utils.ReduceToBason(steps=1, verbose=False)
    mpc_agt = pp.module.MPC(lti_, exp['Q'], exp['p'], T, stepper=stepper_agt) # agent
    x_pred, u_pred, cost_pred = mpc_agt.forward(dt, x_init)
    traj_loss = torch.mean((u_true - u_pred)**2) \
        + torch.mean((x_true - x_pred)**2)
    return traj_loss