Tabular methods for reinforcement learning

PyTorch implementation of the Q-Learning Algorithm Normalized Advantage Function for continuous control problems PER and N-step Method

Open-zero is a research project aiming to realize the various projects of the company DeepMind

This repository contains the code for automatically generating piano fingerings using a reinforcement learning agent that uses Q-Learning.

Turn based strategy game with AI

The objective is to teach robot to find and reach the target object in the minimum number of steps and using the shortest path and avoiding any obstacles such as humans, walls, etc usinf reinforcement learning algorithms.

Q-learning application to find an optimal parking slot

Two intelligent agents (cat and mouse) compete with each other to achieve their goal. Agents are trained through reinforcement learning (Q-learning).

a Python-based platformer infused with Q-Learning and dynamic level creation from simple JSON files.

The implementation for the paper Continuous Deep Q-Learning in Optimal Control Problems: Normalized Advantage Functions Analysis // NeurIPS 2022

This repository contains a Jupyter Notebook with an implemenation of a Q-Learning Agent, which learns to solve the n-Chain OpenAI Gym environment

Demonstration of Q-Learning and SARSA algorithms utilizing Python and OpenAI GYM

🕹️ Welcome to Game-Optimization, a repository dedicated to exploring and implementing various optimization algorithms to solve complex games. This project initially focuses on solving the classic game Sokoban using the Q-learning algorithm, with plans to extend to genetic algorithms and other optimization techniques in the future.

Markov decision process master thesis

Docking robot in a grid environment trained it with Q-learning

This repository contains various networks implementation such as MLP, Hopfield, Kohonen, ART, LVQ1, Genetic algorithms, Adaboost and fuzzy-system, CNN with python.

The 3D bin packing problem is a combinatorial optimization problem that involves fitting a given set of items of various sizes into a container of a specific size such that the total volume of the items is as close to the volume of the container as possible.

Deep Q Learning blackbox strategies for casino games

A collaborative repository for our Bachelor's thesis, focused on optimizing the Cell Outage Compensation (COC) algorithm in Self-Organizing Networks (SONs). Leveraging AI-Hardware Acceleration, the project aims to bolster 5G network reliability, particularly for emerging technologies like autonomous driving.

Dynamic Q-Learning Based Feature Selection approach