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Gym tool use environments.

Project description

Gym Tool Use

gym tool use environments.

$ pip install gym-tool-use


import gym_tool_use  # import to register gym envs
env = gym.make("TrapTube-v0")
observation = env.reset()
action = env.action_space.sample()
observation_next, reward, done, info = env.step(action)
image = env.render(mode="rgb_array")  # also supports mode="human"


The following environments are registered:

  • "TrapTube-v0" (base task)
  • "PerceptualTrapTube-v0"
  • "StructuralTrapTube-v0"
  • "SymbolicTrapTube-v0"
  • "PerceptualSymbolicTrapTube-v0"
  • "StructuralSymbolicTrapTube-v0"
  • "PerceptualStructuralTrapTube-v0"
  • "PerceptualStructuralSymbolicTrapTube-v0"


Baseline implementations here:


Development is started with pipenv.

$ pipenv install
$ pipenv shell

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