class_docstr: A multi-agent abstract class for two player matrix games.
  
  PAYOUT_MATRIX: Numpy array. Along the dimension N, the action of the
  Nth player change. The last dimension is used to select the player
  whose reward you want to know.
  
  max_steps: number of step in one episode
  
  players_ids: list of the RLlib agent id of each player
  
  output_additional_info: ask the environment to aggregate information
  about the last episode and output them as info at the end of the
  episode.
class_docstr_tok: ["A","multi-agent","abstract","class","for","two","player","matrix","games",".","PAYOUT_MATRIX",":","Numpy","array",".","Along","the","dimension","N",",","the","action","of","the","Nth","player","change",".","The","last","dimension","is","used","to","select","the","player","whose","reward","you","want","to","know",".","max_steps",":","number","of","step","in","one","episode","players_ids",":","list","of","the","RLlib","agent","id","of","each","player","output_additional_info",":","ask","the","environment","to","aggregate","information","about","the","last","episode","and","output","them","as","info","at","the","end","of","the","episode","."]
code: def _get_players_rewards(
      self, action_player_0: int, action_player_1: int
  ):
      return [
          self.PAYOUT_MATRIX[action_player_0][action_player_1][0],
          self.PAYOUT_MATRIX[action_player_0][action_player_1][1],
      ]
  
imports: import logging
  from abc import ABC
  from collections import Iterable
  from typing import Dict, Optional
  import numpy
  from gymnasium.spaces import Discrete
  from gymnasium.utils import seeding
  from ray.rllib.env.multi_agent_env import MultiAgentEnv
  from ray.rllib.examples.env.utils.interfaces import InfoAccumulationInterface
  from ray.rllib.examples.env.utils.mixins import TwoPlayersTwoActionsInfoMixin, NPlayersNDiscreteActionsInfoMixin
label_desc: Use image node_id 5 for calling the MatrixSequentialSocialDilemma obj's underlying member method code with example usage: obj._get_players_rewards(action_player_0, action_player_1) and returns: list