# interactive_training

**Repository Path**: mirrors_electronicarts/interactive_training

## Basic Information

- **Project Name**: interactive_training
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: BSD-3-Clause
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-08-08
- **Last Updated**: 2026-03-14

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# 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.