Multi-agent learning (MAL) has emerged as a promising artificial intelligence (AI) and machine learning (ML) paradigm for creating agent-based technologies to develop, secure, and operate cyber-physical-human networks (CPHNs).
Multi-agent learning (MAL) has emerged as a promising artificial intelligence (AI) and machine learning (ML) paradigm for creating agent-based technologies to develop, secure, and operate cyber-physical-human networks (CPHNs).
These members have demonstrated outstanding professional performance, exhibited professional maturity through long-term experience, and established themselves as leaders in their respective IEEE-designated fields of interest.
Participate in the 2025 Low-Resource Audio Codec (LRAC) Challenge, an exciting opportunity to advance the state-of-the-art in neural audio coding for resource-constrained devices.