def optimalWeightFinder(self):
        i = 1
        while True:
            W = self.optimization() # optimize to find new weights in the list of policies
            print ("weights ::", W )
            print ("the distances  ::", self.policiesFE.keys())
            self.currentT = self.policyListUpdater(W, i)
            print ("Current distance (t) is:: ", self.currentT )
            if self.currentT <= self.epsilon: # terminate if the point reached close enough
                break
            i += 1
        return W