Reinforcement learning tutorials

This repository hosts a customized PPO based agent for Carla. The goal of this project is to make it easier to interact with and experiment in Carla with reinforcement learning based agents -- this, by wrapping Carla in a gym like environment that can handle custom reward functions, custom debug output, etc.

Adversarial attacks on Deep Reinforcement Learning (RL)

Deep Reinforcement Learning for Trading

Multi agent gym environment based on the classic Snake game with implementations of various reinforcement learning algorithms in pytorch

💡 Grasp - Pick-and-place with a robotic hand 👨🏻‍💻

Developed a highly customizable OpenAI gym environment and trained a stable_baselines3 PPO agent. Used the expert agent for Imitation Learning with DAgger

Financial trading strategies using deep reinforcement learning (DRL). It offers a frameworks for quantitative finance, enabling practitioners to create, test, and implement investments strategies.

Reinforcement Learning based navigation

State Representations as Incentives for Reinforcement Learning Agents: A Sim2Real Analysis on Robotic Grasping

🚤🏖️BOATS DO VZHHHHH BBBDROOM, BEEEEP, BEEEP, GNAA, HONK, VZHHHHHHHHHHHHHH🏖️🚤

A deep reinforcement learning Bot for https://kana.byha.top:444/

Concept and development of a walking AT-ST Walker (Starwars) ML-agent.

Modular Reinforcement Learning in PyTorch.

AI agent learns to walk, run, hop and crawl with out any given data using proximal policy optimisation.

In this project, I have tried to use DeepRL for optimizing the selection of transactions done by the miner to increase the fee when they execute a block on the chain

AI-driven credit underwriting system combining Machine Learning (ML) & Reinforcement Learning (RL) to optimize loan approvals while managing risk: Credit Risk Prediction via Random Forest model; PPO & DQN for dynamic risk control; Custom OpenAI Gym Environment for simulating real-world lending scenarios & FastAPI real-time processing.

Repository for the final project of the "Computational Intelligence" course @ PoliTo, 2022/2023

Snake game environment integrated with OpenAI Gym. Proximal Policy Optimization (PPO) implementation for training. Visualization of training progress and agent performance. Easy to understand code.

Injecting object-level implicit priors in a PPO agent with contrastive learning algorithm ST-DIM.