Dynamic Leader-Follower Problems: A New Theoretical Framework and a Machine Learning based Computational Approach

University Of Illinois At Chicago, Chicago IL

Investigators

Abstract

Bhattacharya Abstract The objective of this research is to develop reinforcement learning based computational solution methods for dynamic leader-follower problems, and to demonstrate their applicability to problems in regulation and public policy formulation using an example of electricity markets. The approach is to formulate a theoretical framework for dynamic leader-follower problems, which will help characterize different leader-follower type problems important for many application areas, and provide a basis for designing new computational approaches for addressing such applications. Intellectual Merit. In leader-follower problems, the leader seeks an incentive strategy that induces self-interested followers to act in ways that maximize the leaders long-term objective (social welfare). They have wide applicability in dynamic regulation of energy markets, public policy formulation in pollution control, taxation etc. A specific focus of this work is on computational approaches that can work with incomplete information, an aspect not adequately addressed by current approaches. The intellectual merit of this work is in combining recent results from different research streams including competitive sequential decision making, hierarchical games, multi-agent reinforcement learning and stochastic approximation, to develop a new theoretical and computational approach for solving dynamic leader-follower problems. Broader Benefits. The major impact will be through the development and validation of tools for decision making in regulatory and public policy contexts. Such tools will help train professionals in government and non-government agencies in analyzing dynamic regulation and public policy situations and identifying optimal actions. Further, through demonstrating new computational approaches for problems commonly studied in public policy, economics and business, this research will foster interdisciplinary linkages.