Deep RL framework for exploring state spaces of finite state machines.
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Updated
Mar 4, 2022 - Jupyter Notebook
Deep RL framework for exploring state spaces of finite state machines.
PyBullet environments to use Reinforcement learning with Stable Baselines 3
A Guide to Problems and Solutions on Genetic Algorithms
The aim of this repository is the analysis and study of computer intelligence and in-depth learning techniques in the development of intelligent gaming agents.
This project implements an agent for playing the SonicTheHedgehog2 game from a ROM file using the Proximal Policy Optimization (PPO) algorithm from the stablebaselines3 library. The agent is trained to learn the optimal actions to take at each step in the game in order to complete the level and maximize the score.
Distributed training for RL algo on pytorch
Source code for the numerical experiments presented in the paper "On the Unreasonable Efficiency of State Space Clustering in Personalization Tasks".
Superconducting RadioFrequency cavity Frequency Control by Reinforcement Learning
Using Neural Network and Genetic Algorithm to play SnakeGame
Unified framework enabling machine learning-based training, simulation, and deployment of legged robots, compatible with various robot models and reinforcement learning algorithms, with PyBullet simulation and ROS integration.
Autonomous 1:10 race car with a reinforcement learning based approach
Obstacle avoidance agent in a custom Gym environment
My implementation of a reinforcement learning model using Stable-Baselines3 to play the NES Super Mario Bros.
In this project, I created an agent to solve the CartPole task using the stablebaselines3 library. CartPole is a problem from the OpenAI Gym catalog, in which the goal is to maintain balance of a wooden pole using motors attached to its ends. The agent must decide whether to move the pole left or right to maintain balance.
Monorepo for our CV&RL course project: self parking
Train Soft Actor-Critic model for KukaDiverseObject environment in pybullet
An extension of Bomberman game using Multi-Agent Deep Reinforcement Learning with Stable Baselines3, PettingZoo, SuperSuit.
Nokia's classic 'snake' game, written in NumPy and converted into a Gymnasium Environment() for use with gradient-based reinforcement learning algorithms
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