DeepMind Lab is a 3D learning environment based on id Software's Quake III Arena via ioquake3 and other open source software.
DeepMind Lab provides a suite of challenging 3D navigation and puzzle-solving tasks for learning agents. Its primary purpose is to act as a testbed for research in artificial intelligence, especially deep reinforcement learning.
Disclaimer: This is not an official Google product.
If you use DeepMind Lab in your research and would like to cite the DeepMind Lab environment, we suggest you cite the DeepMind Lab paper.
You can reach us at [email protected].
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Get Bazel from bazel.io.
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Clone DeepMind Lab, e.g. by running
$ git clone https://github.com/deepmind/lab
$ cd lab
- For a live example of a random agent, run
lab$ bazel run :random_agent --define headless=false -- \
--length=10000 --width=640 --height=480
Here is some more detailed build documentation, including how to install dependencies if you don't have them.
To test the game using human input controls, run
lab$ bazel run :game -- --level_script tests/demo_map
DeepMind Lab ships with an example random agent in
python/random_agent.py
which can be used as a starting point for implementing a learning agent. To let
this agent interact with DeepMind Lab for training, run
lab$ bazel run :random_agent
The Python API for the agent-environment interaction is described in docs/python_api.md.
DeepMind Lab ships with different levels implementing different tasks. These tasks can be configured using Lua scripts, as described in docs/lua_api.md.