def step(state):
        ''' Predict the action given the current state.
            Novice strategy:
                Case where can gin:
                    Choose one of the gin actions.
                Case where can knock:
                    Choose one of the knock actions.
                Case where can discard:
                    Gin if can. Knock if can.
                    Otherwise, put aside cards in some best meld cluster.
                    Choose one of the remaining cards with highest deadwood value.
                    Discard that card.
                Case otherwise:
                    Choose a random action.

        Args:
            state (numpy.array): an numpy array that represents the current state

        Returns:
            action (int): the action predicted
        '''
        legal_actions = state['legal_actions']
        actions = legal_actions.copy()
        legal_action_events = [ActionEvent.decode_action(x) for x in legal_actions]
        gin_action_events = [x for x in legal_action_events if isinstance(x, GinAction)]
        knock_action_events = [x for x in legal_action_events if isinstance(x, KnockAction)]
        discard_action_events = [x for x in legal_action_events if isinstance(x, DiscardAction)]
        if gin_action_events:
            actions = [x.action_id for x in gin_action_events]
        elif knock_action_events:
            actions = [x.action_id for x in knock_action_events]
        elif discard_action_events:
            best_discards = GinRummyNoviceRuleAgent._get_best_discards(discard_action_events=discard_action_events,
                                                                       state=state)
            if best_discards:
                actions = [DiscardAction(card=card).action_id for card in best_discards]
        if type(actions) == OrderedDict:
            actions = list(actions.keys())
        return np.random.choice(actions)
 Predict the action given the current state.
            Novice strategy:
                Case where can gin:
                    Choose one of the gin actions.
                Case where can knock:
                    Choose one of the knock actions.
                Case where can discard:
                    Gin if can. Knock if can.
                    Otherwise, put aside cards in some best meld cluster.
                    Choose one of the remaining cards with highest deadwood value.
                    Discard that card.
                Case otherwise:
                    Choose a random action.

        Args:
            state (numpy.array): an numpy array that represents the current state

        Returns:
            action (int): the action predicted
        
rlcard/models/gin_rummy_rule_models.py