deal-or-no-deal

Let's play Deal or No Deal better than a human.

What is this?

Deal or No Deal is the greatest TV game show of all time, but for some unknown reason, it does not get a lot of love in the ML community...

... until now!

Why (in audiovisual form)?

See my talk here or just my slides here!

Why (in code form)?

Despite it's simplicity on the surface, Deal or No Deal is a great environment to build a simple supervised model to predict the Banker's model and train a reinforcement learning model in a simple (but tricky) game environment without a clear strategy.

This repo not only contains the data of all decisions made in over 60 episodes of Deal or No Deal, but also:

• A Docker container that installs all necessary requirements to run all the code
• Code to preprocess the TV data into a ML-ready format (deal_or_no_deal/preprocess.py)
• A "random ensemble" supervised machine learning model to input a game state and predict a shockingly close Banker offer (deal_or_no_deal/Banker.py)
• An OpenAI Gym Deal or No Deal environment (deal_or_no_deal/envs/deal_or_no_deal.py)
• Code to train a DQN reinforcement learning agent to explore the Deal or No Deal Environment (deal_or_no_deal/dqn.py)
• Code for an agent to input a game state and play n games in the future, revealing the percentage of future games that end with winnings higher than the current Banker's offer (deal_or_no_deal/fast_play.py)
• A slew of notebooks showing how to interact with all the code (nbs)

Development

Begin by installing Docker if you have not already. Once Docker is running, run development from within the Docker container:

# build the image to extract features
docker build -t deal_or_no_deal .

# run the container in interactive mode on the CPU...
docker run \
    -it \
    --rm \
    -v "${PWD}:/deal_or_no_deal" \
    -p 8888:8888 \
    deal_or_no_deal /bin/bash -c "pip install -r requirements-dev.txt && bash"

To run the Docker container on the GPU, use:

# ... or run the container in interactive mode on the GPU...
docker run \
    -it \
    --rm \
    --gpus all \
    -v "${PWD}:/deal_or_no_deal" \
    -p 8888:8888 \
    deal_or_no_deal /bin/bash -c "pip install -r requirements-dev.txt && bash"

Start JupyterLab

To run JupyterLab, start the container and execute the following:

jupyter lab --ip 0.0.0.0 --no-browser --allow-root --NotebookApp.token='' --NotebookApp.password=''

Connect to JupyterLab here: http://localhost:8888/tree?