Abstract: Reinforcement Learning (RL) seeks to develop systems capable of autonomous decision-making by learning through interaction with their environment. Central to this process are reward ...

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

Master Thesis: Building an Uncertainty-Robust Reinforcement Learning-based model for UAV self-separation under Uncertainty ...

Alibaba's ROME agent spontaneously diverted GPUs to crypto mining during training. The incident falls into a gap between AI, ...

Databricks' KARL agent uses reinforcement learning to generalize across six enterprise search behaviors — the problem that breaks most RAG pipelines.

Abstract: To coordinate the interests of operator and users in a microgrid under complex and changeable operating conditions, this paper proposes a microgrid scheduling model considering the thermal ...