Introduction
In this article, we will continue our series of articles where we are looking at some of the outstanding projects hosted over GitHub repository. This time, our focus will be on GitHub reinforcement learning projects to give you project ideas for yourself. Reinforcement learning has always been a very handy tool in situations where we have insufficient data for training and testing purposes. The projects listed in the article will surely help in understanding different components of reinforcement learning, its operations, and practical implementations in the real world.
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We will also mention the number of stars and forks these Reinforcement GitHub repositories have got at the time of writing this article to measure its popularity.
Reinforcement Learning GitHub Projects Ideas
Connect4 Game Playing by AlphaGo Zero Method |⭐ – 83 | ⑂ – 26
The most popular use of Reinforcement Learning is to make the agent learn how to play different games. This Github repository designs a reinforcement learning agent that learns to play the Connect4 game. Connect4 is a game similar to Tic-Tac-Toe but played vertically and different rules. The author has based their approach on the Deepmind’s AlphaGo Zero method.
Play 2048 using Deep-Reinforcement Learning |⭐ – 152 | ⑂ – 33
2048 is a single-player puzzle game that has become quite popular recently. The game objective is to slide the tiles and merge tiles with a similar number to add them till you create the tile with 2048 or more. The author of this project has created a Convolutional Neural Network which plays the game of 2048 using Deep Reinforcement Learning. This project is really interesting and you should check that out.
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Self-Driving Truck Simulator with Reinforcement Learning |⭐ – 275 | ⑂ – 82
This repository hosts the code for training and running a self-driving truck in Euro Truck Simulator 2 game. This is made achievable by the reinforcement learning-powered AI model that’s made capable to steer, accelerate, and brake the truck as per requirement. The author has taken the basic training approach from the famous Atari Paper and have added small techniques from other papers as well to create this impressive reinforcement learning GitHub project.
Chess Game Playing with AlphaGo Zero methods |⭐ – 1.6k | ⑂ – 393
Chess is a game of mental ability and in early days researchers used to consider Chess as the ultimate game for AI. Media went crazy in 1996 when IBM Deep Blue defeated chess grandmaster Garry Kasparov. But now the chess is a completely solvable game even with rudimentary artificial intelligence approaches. However, chess still attracts people for AI implementation with new methods. This Reinforcement learning GitHub project has created an agent with the AlphaGo Zero method. There are three workers in the AlphaGo Zero method where self-play ensures that the model plays the game for learning about it. The trainer is for training purposes and the evaluator evaluates the performance of the current model with the previous model.
City Bike Rebalancing Problem |⭐ – 12 | ⑂ – 8
This Reinforcement GitHub project looks to solve the bikes rebalancing problem faced by Citi Bike in a city like New York. The rebalancing problem generally arises when bikes(bicycles) are accumulated at lesser-traveled destinations and hotspots are deprived of these bicycles for the users. At present, it is the human operators who estimate manually how to balance the bike distribution throughout the city. The author of this project believes that a reinforcement learning agent can be more precise, timely, and optimized than human agents to solve this problem.
Long Text Generation with LeakGAN |⭐ – 504 | ⑂ – 162
This is a very interesting reinforcement learning project on GitHub that generates long texts with the help of generative adversarial networks for generating desired results. This kind of text generation application can be used in many applications like machine translation, dialogue systems, and image captioning, etc. This project has tried to address some key issues in long text generation by using a new technique called “LeakGAN”.
Video summarization with deep reinforcement learning |⭐ – 228 | ⑂ – 67
This reinforcement learning GitHub project implements AAAI’18 paper – Deep Reinforcement Learning for Unsupervised Video Summarization with Diversity-Representativeness Reward. Built using Python, the repository contains code as well as the data that will be used for training and testing purposes. Interestingly we can also use our own videos for evaluating how our model performs over it.
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Conclusion
We hope this list of GitHub repositories would have given you a good reference point for Reinforcement Learning project ideas. You can either try to improve on these projects or develop your own reinforcement learning projects by taking inspiration from these.
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