Affiliation:
1. King’s College London, United Kingdom
2. Singapore University of Technology and Design, Singapore
3. The Chinese University of Hong Kong, Shenzen, China
Abstract
In multi-agent environments in which coordination is desirable, the history of play often causes lock-in at sub-optimal outcomes. Notoriously, technologies with significant environmental footprint or high social cost persist despite the successful development of more environmentally friendly and/or socially efficient alternatives. The displacement of the status quo is hindered by entrenched economic interests and network effects. To exacerbate matters, the standard mechanism design approaches based on centralized authorities with the capacity to use preferential subsidies to effectively dictate system outcomes are not always applicable to modern decentralized economies. What other types of mechanisms are feasible?
In this article, we develop and analyze a mechanism that induces transitions from inefficient lock-ins to superior alternatives. This mechanism does not exogenously favor one option over another; instead, the phase transition emerges endogenously via a standard evolutionary learning model, Q-learning, where agents trade off exploration and exploitation. Exerting the same transient influence to both the efficient and inefficient technologies encourages exploration and results in irreversible phase transitions and permanent stabilization of the efficient one. On a technical level, our work is based on bifurcation and catastrophe theory, a branch of mathematics that deals with changes in the number and stability properties of equilibria. Critically, our analysis is shown to be structurally robust to significant and even adversarially chosen perturbations to the parameters of both our game and our behavioral model.
Funder
National Research Foundation, Singapore and DSO National Laboratories under its AI Singapore Program
NRF 2018 Fellowship
ALIAS grant
AME Programmatic Fund
Agency for Science, Technology and Research (A*STAR) and Provost’s Chair Professorship
Publisher
Association for Computing Machinery (ACM)
Subject
Computational Mathematics,Marketing,Economics and Econometrics,Statistics and Probability,Computer Science (miscellaneous)