Adversarial attacks on Deep Reinforcement Learning (RL)
-
Updated
Feb 27, 2021 - Jupyter Notebook
Adversarial attacks on Deep Reinforcement Learning (RL)
Deep Reinforcement Learning for Trading
AI agent game competition - Reinforcement learning (Monte Carlo Tree Search, Deep Q-learning, Minimax)
Graduation Project 2023, an intelligent traffic management system that combines reinforcement learning along with simulation.
A simple game aimed at training an artificial agent to play it considerably well.
Reinforcement Learning: Q-Learning and Deep Q-Learning to train artificial agents that can play the famous game of Nim.
Implement the Scripted and DQN Agents for Pysc2 BuildMarines Minigame with PyTorch
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.
FinSearch Research Competition
Deep Learning and Reinforcement Learning in Algorithmic Trading
Reinforcement Learning Project to explore State of the Art RL algorithms and compare their performance for an Agent navigating through an environment while avoiding obstacles.
A game-playing AI that uses Deep-Q Networks to play Checkers
DQN Atari Pong game
My on-going submission to the Kaggle HungryGeese competition where you pit your reinforcement learning agent against other competitors. https://www.kaggle.com/c/hungry-geese
Snake game with RL
Fine-tuning LLM agents w online RL for XiangQi (Chinese Chess)
Deep Reinforcement Learning | Training an AI agent to play Starcraft II
Python code for teaching turtles how to play variations of "tag" with Deep Q-Networks.
Implementation of base DL tasks
Add a description, image, and links to the dqn-agents topic page so that developers can more easily learn about it.
To associate your repository with the dqn-agents topic, visit your repo's landing page and select "manage topics."