Analyzing Bias and Fairness in Multi-Agent AI Systems

This ArXiv article likely examines the challenges of bias and fairness that arise in multi-agent decision systems, focusing on how these emergent properties impact the overall performance and ethical considerations of the systems. Understanding these biases is critical for developing trustworthy and reliable AI in complex environments involving multiple interacting agents.