# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT license.
import numpy as np
from textworld import Agent
[docs]class NaiveAgent(Agent):
def __init__(self, seed=1234):
self.seed = seed
self.rng = np.random.RandomState(self.seed)
self.actions = ["north", "south", "east", "west", "up", "down",
"look", "inventory", "take all", "YES", "wait",
"take", "drop", "eat", "attack"]
[docs] def reset(self, env):
env.display_command_during_render = True
[docs] def act(self, game_state, reward, done):
action = self.rng.choice(self.actions)
if action in ["take", "drop", "eat", "attack"]:
words = game_state.feedback.split() # Observed words.
words = [w for w in words if len(w) > 3] # Ignore most stop words.
if len(words) > 0:
action += " " + self.rng.choice(words)
return action