Game freezing / general robustness to wrapped game engine

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Assessment

Difficulty
4/5
Estimated time
3-5 days
Newbie friendliness
25/100
Issue type
Feature
Clarity
Mostly clear
Activity status
Stale
Tech stack
python
Domain
machine-learning

Research direction

Run the supplied Balances.z5 reproduction first, then inspect textworld.start(...), env.reset(), and env.step() around the wrapped Jericho engine. Done should be demonstrated by the environment reporting a timeout or game-crashed outcome instead of freezing or segfaulting.

Written by the indexing model from the issue text.

Description

bug

I've noticed that when randomly sampling actions in real text games (e.g. ZMachine games not generated by TextWorld), the game inevitably freezes/segfaults at some point (It seems like Jericho has the same issue). Since TextWorld is a RL environment for text games, can we make it more robust to these problems? For example, having a timeout failure or game crashed failure?

Here's a code snippet that consistently freezes on my machine:

# !mkdir -p games
# !wget -q http://www.ifarchive.org/if-archive/games/zcode/Balances.z5 -O games/Balances.z5

import textworld
import itertools
import tqdm
import numpy as np

np.random.seed(0)
episodes = 50
episode_len = 500

scores = []

for episode in range(episodes):
    print('episode {}'.format(episode))
    env = textworld.start('./games/Balances.z5')
    env.reset()
    env.seed(0)
        
    verbs = [w.word for w in env._jericho.get_dictionary() if w.is_verb]
    nouns = [w.word for w in env._jericho.get_dictionary() if w.is_noun]
    actions = [' '.join(tup) for tup in list(itertools.product(verbs, nouns))]
    
    for step in tqdm.trange(episode_len):
        act = np.random.choice(actions)
        print(step, act)
        game_state, score, done = env.step(act)
        if done:
            break
    scores.append(score)
    
print(scores)
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