The future of multi-agent systems: AI that learns to collaborate
Artificial intelligence (AI) is transforming how we address real-world challenges, from diagnosing diseases to personalizing education and enhancing customer service. Reinforcement learning (RL) has already proven its potential by mastering complex board games like Go [1] and fostering cooperation in real-time strategy games like StarCraft [2]. But when multiple AI systems need to work together — or even compete — how do we ensure they achieve the best outcomes for everyone involved? This challenge is at the heart of three recent projects my colleagues and I at Hitachi R&D in Japan and the US have been working on in collaboration with Mila – Quebec AI Institute [3].
