This monograph introduces a comprehensive framework for optimizing perceptual quality in online, real-time, interactive multimedia systems involving multiple users, performance metrics, and application controls. It outlines an integrated offline-online process that learns perceptual quality under controlled conditions and adapts it to dynamic, real-time environments. The optimization is modeled as a decomposable multi-metric, multi-control problem, solvable in polynomial time by integrating solutions from simpler subproblems. Each subproblem is evaluated using a novel, function-free method based on dominance and a binary-divide algorithm with guaranteed error tolerance. The work is the first to show that the relationship between a stimulus and |