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endjinn

ML-powered multi-agent simulation toolkit

Components

  • Main simulation runner
  • Prototypes for Agents, Actions, and Environments
  • Built-in ES solver for policy networks
  • (Coming soon) Javascript action service
  • (Coming soon) Reporter connectors
  • (Coming soon) Real time viz server

Quick start guide

  1. Copy the endjinnfile_proto.json file and rename it endjinnfile.json
  2. Do python setup.py install
  3. Edit parameters in endjinnfile.json to your liking
  4. Do python runsim.py

Note that if you don't use agents and environments which are already present in global_registry.json and have corresponding files, you will need to place your own subclasses in local_registry_objects and ensure that their entries in local_registry.json are complete.

local_registry_objects/ is ignored by Git, so you may need to create the directory.

Similarly, local_registry.json is ignored. If you want to create custom objects, copy local_registry_proto.json, rename it to local_registry.json, and edit its fields to reflect your custom objects.

Wiki entry here: https://github.com/MaxwellRebo/endjinn/wiki/Local-registry-explained

Running Tests

nosetests --nologcapture

Drop nologcapture if you prefer to use nose's standard capturing. However, note that in its standard mode it is likely to spit out a bunch of Tensorflow log messages before proceeding to the tests.

Dependencies

  • Numpy
  • Keras (TF backend)
  • Tensorflow

See here for instructions on how to install Tensorflow on your target OS. Note that CUDA is required.

Note on TF/CUDA: While a GPU is not required for training due to use of Evolution Strategies solver, TF backend must be present for Keras models to compile correctly.

Overview & Tips

  • Main objects are Environment, Agent, and Action.
  • Each object can be sub-classed and placed in registry_objects
  • To use local files, edit the local_registry.json file
  • local_registry.json objects will be looked for in local_registry_objects. Both the registry file and the directory are ignored by default, so you won't end up accidentally publishing your local work to the main repo.
  • To add a global object (Action, Agent, Environment), edit the registry, make sure all files are in registry_objects, and do a pull request

Roadmap

  • Global registry will eventually get moved to Endjinn Package Manager (EPM)
  • Additional Object Packs for different simulation domains will be added over time
  • Work on additional policy types and solvers is ongoing, look for periodic updates
  • OpenMPI-based distributed processing

For suggestions please start an issue. Gitter forthcoming.

Additional Info

The wiki will be frequently updated with more in-depth guides and info:

https://github.com/MaxwellRebo/endjinn/wiki

Check back periodically.

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ML-powered multi-agent simulation toolkit

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