alpaca/alpacka/agents/stochastic_mcts.py
def reset(self, env, observation):
        """Reinitializes the search tree for a new environment."""
        del observation
        assert env.action_space == self._action_space
        self._model = env
        # Initialize root with some reward to avoid division by zero.
        self._root = TreeNode(init_reward=0)
        self._real_visited = set()
Reinitializes the search tree for a new environment.
Reinitializes the search tree for a new environment.
Reinitializes the search tree for a new environment .
def reset(self, env, observation):
        del observation
        assert env.action_space == self._action_space
        self._model = env
        self._root = TreeNode(init_reward=0)
        self._real_visited = set()
def reset ( self , env , observation ) : del observation assert env . action_space == self . _action_space self . _model = env self . _root = TreeNode ( init_reward = 0 ) self . _real_visited = set ( )
Reinitializes the search tree for a new environment.
Reinitializes the search tree for a new environment .
"""Reinitializes the search tree for a new environment.""" # Initialize root with some reward to avoid division by zero.
self
env
observation