Multi-Agent Reinforcement Learning (MARL) is an emerging subfield of artificial intelligence that investigates how multiple autonomous agents can learn collaboratively and competitively within an ...

Conventional water quality surveillance relies heavily on manual sampling, localized sensors, and intermittent laboratory ...

Discover how multi-agent AI systems are transforming industries with real-time optimization and collaboration, guided by Andrew Ng’s insights.

The next leap is evolving how we think about AI. We need AI that thinks, adapts, and collaborates. This is the promise of ...

Erev, Ido, and Alvin E. Roth. "Multi-agent Learning and the Descriptive Value of Simple Models." Special Issue on Foundations of Multi-Agent Learning. Artificial Intelligence 171, no. 7 (May 2007): ...

Instead of retraining the LLM, the agent consults a dynamic store of past outcomes to make smarter decisions for new tasks.

Yixin (02858.HK) is an AI-driven fintech platform. "Yixin Smart Service" is a one-stop AI intelligent service solution developed by Yixin, aimed at solving the AI application challenges faced by ...

The Journal of the Operational Research Society, Vol. 62, No. 2, Special Issue: Heuristic Optimisation (February 2011), pp. 281-290 (10 pages) Intelligent optimization refers to the promising ...

Multi-armed bandits (MAB) is a peculiar Reinforcement Learning (RL) problem that has wide applications and is gaining popularity. Multi-armed bandits extend RL by ignoring the state and try to balance ...