animalai

Hotfix for curriculum which was loading in the wrong order

Add curriculum learning to `animalai-train` to use yaml configurations

- v1.0.5
- Adds customisable resolution during evaluation
- Update `animalai-train` to tf 1.14 to fix `gin` broken dependency
- Release source code for the environment (no support to be provided on this for now)
- Fixes some legacy dependencies and typos in both libraries

- v1.0.3
- Adds inference mode to Gym environment
- Adds seed to Gym Environment
- Submission example folder containing a trained agent
- Provide submission details for the competition
- Documentation for training on AWS

Plus previous additions not tagged as release:

- v1.0.2
- Adds custom resolution for docker training as well
- Fix version checker

- v1.0.0
- Adds custom resolution to both Unity and Gym environments
- Adds inference mode to the environment to visualise trained agents
- Prizes announced
- More details about the competition

- Adds score in playmode (current and previous scores)
- Playmode now incorporates lights off directly (in `examples` try: `python visualizeArena.py configs/lightsOff.yaml`)
- To simplify the environment several unnecessary objects have been removed [see here](documentation/definitionsOfObjects.md)
- **Several object properties have been changed** [also here](documentation/definitionsOfObjects.md)
- Frames per action reduced from 5 to 3 (*i.e.*: for each action you send we repeat it for a certain number of frames
to ensure smooth physics)
- Add versions compatibility check between the environment and API
- Remove `step_number` argument from `animalai.environment.step`

- v0.5 Package `animalai`, gym compatible, dopamine example, bug fixes
- Separate environment API and training API in Python
- Release both as `animalai` and `animalai-train` PyPI packages (for `pip` installs)
- Agent speed in play-mode constant across various platforms
- Provide Gym environment
- Add `trainBaselines,py` to train using `dopamine` and the Gym wrapper
- Create the `agent.py` interface for agents submission
- Add the `HotZone` object (equivalent to the red zone but without death)