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Flatland is simple and efficient grid world for multi-agent reinfrocement learning tasks. It allows for a diverse set of problem classes to be implemented from free moving agents to restricted movement on transportation networks.
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Flatland is simple and efficient grid world for multi-agent reinfrocement learning tasks. It allows for a diverse set of problem classes to be implemented from free moving agents to restricted movement on transportation networks.
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## How to get started
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## Documentation
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To get started with the **Flatland** environment follow the steps in [installation](Installation) and look at the [examples](Examples).
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The documentation can be found at <http://flatland-rl-docs.s3-website.eu-central-1.amazonaws.com>.
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## Specifications
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- [Overview](Specifications/Overview)
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- [Core](Specifications/Core)
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- [Rendering](Specifications/Rendering)
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- [Environment](Specifications/Environment)
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- [Railway](Specifications/Railway)
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## Baselines
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- [Single Agent Navigation](Baselines/Single Agent Navigation)
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- [Multi Agent Navigation](Baselines/Multi Agent Navigation)
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## Integrations Tests
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- [Tests](Tests)
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## Links and Files
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## Links and Files
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