Mount Sinai study multi-agent AI shows higher accuracy and lower computing use managing up to 80 clinical tasks simultaneously in simulations.

Training standard AI models against a diverse pool of opponents — rather than building complex hardcoded coordination rules — ...

Abstract: Cooperative perception has significant potential to enhance perception performance compared to single-agent systems by integrating information from multiple agents through ...

Abstract: We present a distributed source-seeking and flocking control method for networked multi-agent systems with non-holonomic constraints. Based solely on identical on-board sensor systems, which ...