As the electricity market is progressively liberalized, virtual bidding has emerged as a novel participation mechanism attracting increasing attention. This paper integrates evolutionary game theory ...

Training standard AI models against a diverse pool of opponents — rather than building complex hardcoded coordination rules — is enough to produce cooperative multi-agent systems that adapt to each ...

However, a new study finds that one of the most critical challenges facing these systems is not performance or accuracy alone ...

We used Tonic Fabricate to generate a fully synthetic email corpus, then RL fine-tuned an open-source model against it. The ...

Reinforcement learning is a subfield of machine learning concerned with how an intelligent agent can learn through trial and error to make optimal decisions in its ...

Reinforcement Learning (RL) has rapidly emerged as a powerful approach for enabling robots to acquire adaptive, data-driven behaviors in real-world ...