Taming MAML: efficient unbiased meta-reinforcement learning

An Intelligent Traffic Light Control system using Reinforcement Learning. Compares Deep Q-Network (DQN) and Tabular Q-Learning to optimize traffic flow in SUMO simulator.

Building the strong structured code and using FinRL to find the best configurations of agent for multistock trading

A simple reinforcement learning example using tabular Q-learning to teach an agent to navigate a 5×5 grid from the top-left corner to the bottom-right corner, avoiding obstacles along the way.

Implementation of Proximal Policy Optimization (PPO) applied to Super Mario Bros using PyTorch.

Project for a class in the Bachelor degree in Informatics and Multimedia Engineering