Microsoft

Agent Lightning

We present Agent Lightning (opens in new tab), a flexible and extensible framework that enables seamless agent optimization for any existing agent framework. Here agent optimization includes various ...
Microsoft

Microsoft at NeurIPS 2024: Advancing AI research across domains

The event gathers researchers, industry leaders, and practitioners to exchange ideas, address challenges, and advance innovations to shape the future of AI. Lidong Zhou, managing director of Microsoft ...
GitHub

R3DM: Enabling Role Discovery and Diversity Through Dynamics Models in Multi-agent Reinforcement Learning

This repository contains the official implementation for R3DM accepted at the International Conference on Machine Learning (ICML) 2025. It includes the source code for the ACORM and R3DM algorithms, ...
IEEE

Formation and Obstacle Avoidance Control Based on Multi-Agent Reinforcement Learning

Abstract: For the multi-agent formation control problem, the current mainstream control methods are based on graph theory and consistency theory, which often require precise modeling of the system and ...
IEEE

Human Strategy Learning-Based Multi-Agent Deep Reinforcement Learning for Online Team Sports Game

Abstract: In 3 vs. 3 online basketball games, finite state machine (FSM)-based Game artificial intelligence (AI) has traditionally been employed. However, limitations such as repetitive behavior ...
SiliconANGLE

AWS simplifies AI agent customization with automated reinforcement learning

Amazon Web Services Inc. wants to solve the efficiency challenges of artificial intelligence agents and reduce their overall inference demands, and it’s tackling the problem with more advanced model ...