Interactive Training

The repository provides two minimal examples of Markov Ensemble discussed in the paper "Towards Interactive Training of Non-Player Characters in Video Games" (http://arxiv.org/abs/1906.00535) presented at 2019 ICML Workshop on Human in the Loop Learning (HILL 2019), Long Beach, USA.

Credits

• Igor Borovikov - iborovikov@ea.com
• Jesse Harder - jharder@ea.com

Project Structure

• common/ - a source of code files used throughout the project.
• examples/ - contains two example demonstrations that can be run: lunar_lander and mountain_car.
• notebooks/ - contains a Jupyter Notebook and various files produced by the notebook regarding performance in the example environments.

Running Examples

To run the examples in this project, navigate to the desired folder under examples/. Within either lunar_lander/ or mountain_car/, run python interactively_trainable_agent.py. Each folder contains a readme with more information on running that example.

License

Modified BSD License (3-Clause BSD license) see the file LICENSE in the project root.