Implementation Cost and Efficiency for AI Experience Managers

Abstract

The study of Artificial Intelligence (AI) experience managers seeks to create software agents that can support compelling, interactive user experiences without needing any online guidance from human experts. Evaluating the utility of such AI managers is important in both academia and industry, both for measuring our progress in the field and for estimating a given manager's practical viability. While several methods have been studied that evaluate a manager's effectiveness, relatively few have explored the question of how costly a manager might be to implement in practice. We explore the latter question in this paper, presenting a formal way to estimate the cost of implementing an AI experience manager at scale.