Behavioral Analytics for Myopic Agents

Mintz, Yonatan & Aswani, Anil & Kaminsky, Philip & Fukuoka, Yoshimi. (2017). Behavioral Analytics for Myopic Agents. European Journal of Operational Research. 310. 10.1016/j.ejor.2023.03.034.

Many multi-agent systems have a single coordinator providing incentives to a large number of agents. Two challenges faced by the coordinator are a finite budget from which to allocate incentives, and an initial lack of knowledge about the utility function of the agents. Here, we present a behavioral analytics approach for solving the coordinator’s problem when the agents make decisions by maximizing utility functions that depend on prior system states, inputs, and other parameters that are initially unknown. Our behavioral analytics framework involves three steps: first, we develop a model that describes the decision-making process of an agent; second, we use data to estimate the model parameters for each agent and predict their future decisions; and third, we use these predictions to optimize a set of incentives that will be provided to each agent. The framework and approaches we propose in this paper can then …