@inproceedings{f63bf8a30aa743fc889f6dd1c55d15d5,
title = "A game-theoretic formulation of the homogeneous self-reconfiguration problem",
abstract = "In this paper we formulate the homogeneous two- and three-dimensional self-reconfiguration problem over discrete grids as a constrained potential game. We develop a game-theoretic learning algorithm based on the Metropolis-Hastings algorithm that solves the self-reconfiguration problem in a globally optimal fashion. Both a centralized and a fully decentralized algorithm are presented and we show that the only stochastically stable state is the potential function maximizer, i.e. the desired target configuration. These algorithms compute transition probabilities in such a way that even though each agent acts in a self-interested way, the overall collective goal of self-reconfiguration is achieved. Simulation results confirm the feasibility of our approach and show convergence to desired target configurations.",
author = "Daniel Pickem and Magnus Egerstedt and Shamma, \{Jeff S.\}",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE. Copyright: Copyright 2017 Elsevier B.V., All rights reserved.; 54th IEEE Conference on Decision and Control, CDC 2015 ; Conference date: 15-12-2015 Through 18-12-2015",
year = "2015",
month = feb,
day = "8",
doi = "10.1109/CDC.2015.7402645",
language = "English (US)",
series = "Proceedings of the IEEE Conference on Decision and Control",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2829--2834",
booktitle = "54rd IEEE Conference on Decision and Control,CDC 2015",
address = "United States",
}