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PyBullet CartPole and Quadrotor environments—with CasADi symbolic a priori dynamics—for learning-based control and RL
PyBullet Gymnasium environments for single and multi-agent reinforcement learning of quadcopter control
Repository associated with paper titled "AMSwarm: An Alternating Minimization Approach for Safe Motion Planning of Quadrotor Swarms in Cluttered Environments", presented at IEEE ICRA 2023.
Autonomous UAV Navigation without Collision using Visual Information in Airsim
One repository is all that is necessary for Multi-agent Reinforcement Learning (MARL)
[IEEE ICUAS 2022] Python scripts for swarming, formation control, and observer-based adversary detection for multi-UAVs (Tello Drones)
A drone swarm simulator based on ROS (Robot Operating System).
An Efficient Framework for Fast UAV Exploration
Rapid Exploration with Multiple Unmanned Aerial Vehicles (UAV)
[ICRA'24 Best UAV Paper Award Finalist] An Efficient Global Planner for Aerial Coverage
(ICML 2023) Feature learning in deep classifiers through Intermediate Neural Collapse: Accompanying code
This is the homepage of a new book entitled "Mathematical Foundations of Reinforcement Learning."
Lipschitz-constrained Unsupervised Skill Discovery (ICLR 2022)
This is the official implementation of Multi-Agent PPO (MAPPO).
Deep Reinforcement Learning codes for study. Currently, there are only codes for algorithms: DQN, C51, QR-DQN, IQN, QUOTA.
Distributional Policy Optimization: An Alternative Approach for Continuous Control
Code accompanying NeurIPS 2019 paper: "Distributional Policy Optimization - An Alternative Approach for Continuous Control"
Grandmaster-Level Chess Without Search
A curated list of Multi-Modal Reinforcement Learning resources (continually updated)
A curated list of Diffusion Model in RL resources (continually updated)
Python library for solving reinforcement learning (RL) problems using generative models (e.g. Diffusion Models).
[NeurIPS 2023 Spotlight] LightZero: A Unified Benchmark for Monte Carlo Tree Search in General Sequential Decision Scenarios (awesome MCTS)
off policy proximal policy optimization implementation
An application of ideas from control theory to hopefully accelerate the dynamics of TD learning.