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 ...

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

Researchers have developed a new artificial intelligence approach that exposes critical weaknesses in multi-agent reinforcement learning systems, enabling stronger coordinated attacks with broad ...

A reinforcement learning environment is a fail-safe digital practice room where an agent can afford to make mistakes and ...

Researchers at the Japan Advanced Institute of Science and Technology (JAIST) implemented a framework named PenGym that supports the creation of realistic training environments for reinforcement ...

A research team behind an autonomous AI agent said that the model unexpectedly attempted to use computing resources for ...

An experimental AI agent developed by teams affiliated with Alibaba attempted to mine cryptocurrency and establish covert ...

Alibaba-linked AI agent ROME independently mined cryptocurrency and opened unauthorized SSH tunnels during training, raising concerns about AI autonomy.