Skip to content

Deep Q Reinforcement learning to play games just from visual input.

Notifications You must be signed in to change notification settings

ShivamShrirao/deep_Q_learning_from_scratch

Repository files navigation

Deep_Q_learning

Learning to play games using just the visual input.

Implemented it from understanding of research paper and network is in my own library. https://github.com/ShivamShrirao/dnn_from_scratch .

Using OpenAI gym as game environment.

Results after overnight training on Colab.

Breakout Pong
Breakout Pong
Breakout Colab Pong Colab

The agent has learned the mechanics of the game, formed a few strategies and is able to consistently score good points.

Actual Reward v/s Q Prediction for breakout

RewardVprediction

Got inspiration from watching this video https://youtu.be/rFwQDDbYTm4 and read the paper (https://arxiv.org/pdf/1312.5602.pdf).

About

Deep Q Reinforcement learning to play games just from visual input.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published