Tabular methods for reinforcement learning
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Updated
Jul 3, 2020 - Python
Tabular methods for reinforcement learning
path planning using Q learning algorithm
The following project concerns the development of an intelligent agent for the famous game produced by Nintendo Super Mario Bros. More in detail: the goal of this project was to design, implement and train an agent with the Q-learning reinforcement learning algorithm.
Demonstration of Q-Learning and SARSA algorithms utilizing Python and OpenAI GYM
This github contains a simple OpenAi Gym Maze Enviroment and (at now) a RL Algorithm to solve it.
Applying PBT optimization technique to different domains
Implementation of SARSA algorithm for path planning
Implementing Reinforcement Learning (RL) Algorithms for global path planning in tasks of mobile robot navigation.
Reinforcement learning system using the SARSA-RL Algorithm to learn to play a simple physics game, referred to as the The Acrobat Game
Pac-Man RL Agent
Ludo-RL è un progetto che ha visto lo sviluppo e l'implementazione di un sistema di apprendimento per rinforzo finalizzato al gioco da tavolo Ludo.
Implementation of an agent capable of playing a simplified version of the blackjack game using SARSA algorithm.
人工智能课程的实验
Various Reinforcement Learning Algorithms on Racetrack Simulations
PacmanRL - Reinforcement Learning for Pacman (Q-Learning / SARSA)
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