universe-starter-agent The codebase implements a starter agent that can solve a number of environments. It contains a basic implementation of the A3C algorithm, adapted for real-time environments. Dependencies Python 2.7 or 3.5 six (for py2/3 compatibility) TensorFlow 0.11 tmux (the start script opens up a tmux session with multiple windows) htop (shown in one of the tmux windows) gym gym[atari] universe opencv-python numpy scipy Getting Started Add the following to your so that you'll have the correct environment when the script spawns new bash shells Atari Pong The
| Stars | 7 |
| Forks | 2 |
| Language | Python |
| Category | AI 工具 |
| License | MIT |
| Quality Score | 37.7/100 |
| Last Updated | 2017-02-18 |
| Created | 2017-02-06 |
| Platforms | python |
| Est. Tokens | ~161k |
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openai-universe-agents is Deep reinforcement learning agents for OpenAI universe environments. It is categorized as a AI 工具 with 7 GitHub stars.
openai-universe-agents is primarily written in Python. It covers topics such as ai, algorithm, algorithms.
You can find installation instructions and usage details in the openai-universe-agents GitHub repository at github.com/futurely/openai-universe-agents. The project has 7 stars and 2 forks, indicating an active community.
openai-universe-agents is released under the MIT license, making it free to use and modify according to the license terms.