Let’s look at how RL agents are trained to deal with ambiguity, and it may provide a blueprint of leadership lessons to ...

The rise of AI agents in everyday banking represents a transformative shift in how financial services are delivered and experienced. By enabling autonomous transaction handling, intelligent ...

What's new? Kimi K2.5 is an open-source multimodal model on Kimi.com, Kimi App, API and Kimi Code; its agent swarm with 100 subagents executes 1,500 tool calls in beta.

Over the past few years, AI systems have become much better at discerning images, generating language, and performing tasks within physical and virtual environments. Yet they still fail in ways that ...

Abstract: This letter investigates a multi-user multi-input single-output (MISO) system assisted by movable antennas (MAs) and the reconfigurable intelligent surface (RIS). Specifically, the positions ...

Multi-AI agents – multiple artificial intelligence agents working together in a shared environment – can be used to address persistent workflow challenges in clinical decision support, drawing from ...

Today's AI agents don't meet the definition of true agents. Key missing elements are reinforcement learning and complex memory. It will take at least five years to get AI agents where they need to be.

Introduction: The ability of artificial agents to dynamically adapt their communication style is a key factor in sustaining engagement during human-agent interaction. This study introduces a ...

Abstract: Designing effective reward functions is fundamental challenging in reinforcement learning, especially in complex multi-agent systems with intricate credit assignment. Preference-based ...