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An AI agent capable of solving OpenAI Gym's Lunar Lander problem using Deep Reinforcement Learning

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Description

The code written for this report is in Python 3.6

The major dependencies are Numpy, Matplotlib, OpenAI gym with PyBox2D, and PyTorch

A full output of the virtual environment dependencies is listed below as a pip freeze output

Usage:

Grader should run train.py if they wish to train a baseline model

Grader should run graph.py to visualize training or test curves

Grader should run run.py to see baseline model run on test data

All other files are supplementary

Full dependencies:

args==0.1.0 Box2D==2.3.1 certifi==2018.8.24 cffi==1.11.5 chardet==3.0.4 click==6.7 clint==0.5.1 cycler==0.10.0 Django==2.0.1 floyd-cli==0.11.11 future==0.16.0 gym==0.10.8 idna==2.7 kiwisolver==1.0.1 marshmallow==2.16.1 matplotlib==3.0.0 mkl-fft==1.0.6 mkl-random==1.0.1 numpy==1.15.2 olefile==0.46 pathlib2==2.3.2 Pillow==5.2.0 pycparser==2.19 pyglet==1.3.2 pyparsing==2.2.1 python-dateutil==2.7.3 pytz==2017.3 PyYAML==3.13 raven==6.9.0 requests==2.19.1 requests-toolbelt==0.8.0 scipy==1.1.0 six==1.11.0 tabulate==0.8.2 torch==0.4.1.post2 torchvision==0.2.1 tornado==5.1.1 urllib3==1.23 virtualenv==16.0.0

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An AI agent capable of solving OpenAI Gym's Lunar Lander problem using Deep Reinforcement Learning

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