Implementation of base DL tasks
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Updated
Jun 11, 2024 - Jupyter Notebook
Implementation of base DL tasks
Python library for Reinforcement Learning.
Code repository with classical reinforcement learning and deep reinforcement learning methods for Pokémon battles in Pokémon Showdown.
The AI solves a maze using Q Learning
Collection of Machine Learning Algorithms
This is a project for the course Inteligent Systems (IF684) in CIN-UFPE. Basically it's the implementation of q learning, which is a reinforcement learning algorithm, the objective is use it to training the Amongus to learn the fastest way to arrive at the end of the map.
Implementing DeepQNetwork and Q learning on gymnasium CartPole-V1 env.
Automated analysis of hyperparameter configurations for n-step Q-Learning reinforcement agents
Implemented the Q-learning algorithm to solve the MountainCar environment . The MountainCar problem involves a car trying to reach a flag on top of a hill, with the challenge being that the car's engine is not strong enough to drive straight up. Instead, it must learn to use the momentum of going back and forth to reach the goal.
Implementación de Técnicas de Aprendizaje por Refuerzo mediante el algoritmo Q-Learning para la cátedra Inteligencia Artificial (Ciclo 2013) perteneciente a UTN Facultad Regional Resistencia.
The Q-Learning Path Calculator is a Python-based application that utilizes Q-learning to find the shortest path for a robot on a given maze.
Tutorial4RL: Tutorial for Reinforcement Learning. 强化学习入门教程.
C++ implementation of the Q-Learning algorithm applied to a simple grid world problem
The Fundamentals of Artificial Intelligence Course Projects.
Reinforcement Learning solution to OpenAI’s Gym CartPole-v1
Deep reinforcement learning experiments
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