GitHub

niran1717/Multi-Agent-Deep-Deterministic-Policy-Gradient-MADDPG-for-Cooperative-Multi-Agent-Learning

maddpg_project/ │ main.py # Training entry point │ requirements.txt # All dependencies │ ├───maddpg/ # Core MADDPG components │ actor.py │ agent.py │ critic.py │ replay_buffer.py │ utils.py │ __init__ ...
IEEE

Optimization of Task Scheduling Strategy With Timing and Data Dependencies in VEC Based on Deep Reinforcement Learning

Abstract: In the Internet of Vehicles (IoV), the large number of computation tasks generated by intelligent vehicles can usually be decomposed into multiple subtasks with timing and data dependencies.
IEEE

Toward Energy Efficiency and Fairness in UAV-Based Task Offloading

Abstract: The rising demand for compute-intensive mobile applications challenges the limited energy and processing power of user equipment (UE). While Mobile Edge Computing (MEC) enables task ...
GitHub

Ephrame-A/Multi_agent-warehouse-RL

This project implements a robust Multi-Agent Reinforcement Learning (MARL) environment for warehouse robotics research and experimentation. It supports both Independent Q-Learning (IQL) and MADDPG ...
Investopedia

Algorithmic Trading Explained: Methods, Benefits, and Drawbacks

James Chen, CMT is an expert trader, investment adviser, and global market strategist. Gordon Scott has been an active investor and technical analyst or 20+ years. He is a Chartered Market Technician ...
Investopedia

Artificial Intelligence (AI): What It Is, How It Works, Types, and Uses

Investopedia contributors come from a range of backgrounds, and over 25 years there have been thousands of expert writers and editors who have contributed. Gordon Scott has been an active investor and ...