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.ipynb_checkpoints
config
game
model
src
vocab
weights
.gitignore
README.md
agent.py
custom_agent.py
env.py
eval.py
navigator.py
notebook_controller.py
requirements.txt
test.ipynb
train.py
utils.py

README.md

LeDeepChef alt text - Deep Reinforcement Learning Agent for Families of Text-Based Games

This is the repository to the runner-up model in the First TextWorld Problems: A Reinforcement and Language Learning Challenge, called LeDeepChef alt text.

Setup

To setup the repository follow these steps:

  1. Make sure virtualenv is installed
    pip3 install --user virtualenv

  2. Create a new virtual environment called "venv_ftwp"
    python -m virtualenv venv_ftwp

  3. Activate the virtual environment
    source venv_ftwp/bin/activate

  4. install all requirements by running the following command inside the root folder
    pip install -r requirements.txt

Manually Evaluate the Model

There is an IPython notebook text.ipynb in which you can play one instance of a TextWorld game. While playing through the game you see how the DeepChef agent constructs possible commands and ranks them based on the provided context.

This is how it looks like: Example of the notebook test.ipynb

Train the model

The weigths/ folder already provides a trained instance of the agent, that scores at around 90% of the maximum score at an average game. In case you want to train your own agent, use the folloiwing command:

python train.py --games <path/to/traininggames>

Note: Training games are not part of this repo, but can be found on the TextWorld homepage.

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