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Reinforcement Learning

Search Algorithms

This project explains how some searching algorithms works, such as local search, A* and other algorithms.

A project based on the Lunar Lander environment from OpenAI Gym, the goal is to make the rocket land on the moon between the two flags of the environment, the algorithm is built based on Q-Learning and Deep-Q-Learning, using neural networks with tensorflow to train the agent with as many episodes as the developer wants.

A project based on the Taxi Driver environment from OpenAI Gym, the idea is to drive a taxi car to catch up a passenger and drive him to the passenger destination.

In this project, the idea was to build a algorithm that solves the 8 Puzzle Problem using A* algorithm.

A connect 4 player project using reinforcement learning with MinMax algorithm using pygame to build the interactive interface.

This project is just a document that explains some of the main algorithms that are used on reinforcement learning algorithms and projects.

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