Starred repositories
Your own personal AI assistant. Any OS. Any Platform. The lobster way. 🦞
Code for paper "A Large Language Model-Driven Reward Design Framework via Dynamic Feedback for Reinforcement Learning"
[AAAI-25] Latent Reward: LLM-Empowered Credit Assignment in Episodic Reinforcement Learning.
Simulation Code for Z. Wang, J. Zhang, H. Lei, D. Niyato, and Bo Ai, "Optimal Bilinear Equalizer Beamforming Design for Cell-Free Massive MIMO Networks with Arbitrary Channel Estimators," in IEEE T…
Simulation code for "Cell-Free Massive MIMO in O-RAN: Energy-Aware Joint Orchestration of Cloud, Fronthaul, and Radio Resources," by Özlem Tuğfe Demir, Meysam Masoudi, Emil Björnson, and Cicek Cavd…
Simulation code for “Joint Power Control and LSFD for Wireless-Powered Cell-Free Massive MIMO,” by Özlem Tuğfe Demir and Emil Björnson, IEEE Transactions on Wireless Communications, vol. 20, no. 3,…
Simulation code for “Performance of Cell-Free Massive MIMO with Rician Fading and Phase Shifts,” by Özgecan Özdogan, Emil Björnson, Jiayi Zhang, IEEE Transactions on Wireless Communications, vol. 1…
Cell-free Massive MIMO Meets OTFS Modulation
Simulation code for “Scalable Cell-Free Massive MIMO Systems,” by Emil Björnson and Luca Sanguinetti, IEEE Transactions on Communications, to appear.
Simulation code for “Learning-Based Downlink Power Allocation in Cell-Free Massive MIMO Systems,” by Mahmoud Zaher, Özlem Tuğfe Demir, Emil Björnson, Marina Petrova, IEEE Transactions on Wireless C…
Simulation code for “Making Cell-Free Massive MIMO Competitive With MMSE Processing and Centralized Implementation,” by Emil Björnson and Luca Sanguinetti, IEEE Transactions on Wireless Communicati…
Book PDF and simulation code for the monograph "Foundations of User-Centric Cell-Free Massive MIMO" by Özlem Tugfe Demir, Emil Björnson and Luca Sanguinetti, published in Foundations and Trends in …
Collection of reinforcement learning algorithms
Implementation of the Deep Deterministic Policy Gradient (DDPG) using PyTorch
Teaching a quadcopter to fly using Reinforcement Learning (DDPG algorithm) in Pytorch
Light‑weight, strictly‑typed Python toolkit for 6‑DoF quadrotor simulation, 3‑D plotting and step‑wise control loops — perfect for control‑systems classes, flight‑code prototyping or RL research.
Train a quadcopter to fly with a deep reinforcement learning algorithm - DDPG
What Matters in Learning A Zero-Shot Sim-to-Real RL Policy for Quadrotor Control? A Comprehensive Study
PyBullet Gymnasium environments for single and multi-agent reinforcement learning of quadcopter control
四轴飞行器或四轴飞行器无人机在个人和专业应用领域都变得越来越热门。它易于操控，并广泛应用于各个领域，从最后一公里投递到电影摄影，从杂技表演到搜救，无所不包。
udacity final project. teach a quadcopter to fly using reinforcement learning
Udacity Deep Learning Nano Degree Project : Deep Reinforcement Learning Based Quadcopter controller
Teach a Quadcopter How to Fly!
Reinforcement Learning for quadrotor trajectory planning and control