The Role of Population Games and Evolutionary Dynamics in Distributed Control Systems: The Advantages of Evolutionary Game Theory

Recently, there has been an increasing interest in the control community in studying large-scale distributed systems. Several techniques have been developed to address the main challenges for these systems, such as the amount of information needed to guarantee the proper operation of the system, the economic costs associated with the required communication structure, and the high computational burden of solving for the control inputs for largescale systems.

[1]  Anastasios I. Dounis,et al.  Intelligent control system for reconciliation of the energy savings with comfort in buildings using soft computing techniques , 2011 .

[2]  Michael Wooldridge,et al.  Game Theory and Decision Theory in Multi-Agent Systems , 2002, Autonomous Agents and Multi-Agent Systems.

[3]  Walid Saad,et al.  Game Theory for Networks: A tutorial on game-theoretic tools for emerging signal processing applications , 2016, IEEE Signal Processing Magazine.

[4]  Kevin M. Passino,et al.  Illumination Balancing Algorithm for Smart Lights , 2014, IEEE Transactions on Control Systems Technology.

[5]  Ronald Aylmer Sir Fisher,et al.  The genetical theory of natural selection: a complete variorum edition. , 1999 .

[6]  William H. Sandholm,et al.  Population Games And Evolutionary Dynamics , 2010, Economic learning and social evolution.

[7]  J.A.P. Lopes,et al.  Defining control strategies for MicroGrids islanded operation , 2006, IEEE Transactions on Power Systems.

[8]  Nicanor Quijano,et al.  Constrained distributed optimization: A population dynamics approach , 2016, Autom..

[9]  Nicanor Quijano,et al.  Dynamic bandwidth allocation in wireless networks using a Shahshahani gradient based extremum seeking control , 2012, 2012 6th International Conference on Network Games, Control and Optimization (NetGCooP).

[10]  Carlos Ocampo-Martinez,et al.  Model Predictive Control of Wastewater Systems , 2010 .

[11]  Nicanor Quijano,et al.  A population dynamics approach for the water distribution problem , 2010, Int. J. Control.

[12]  Jason R. Marden,et al.  Designing games for distributed optimization with a time varying communication graph , 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

[13]  Stephen V. Samouhos,et al.  Intelligent Infrastructure for Energy Efficiency , 2010, Science.

[14]  Andres Pantoja,et al.  Building Temperature Control Based on Population Dynamics , 2014, IEEE Transactions on Control Systems Technology.

[15]  Michael J. Smith,et al.  The Stability of a Dynamic Model of Traffic Assignment - An Application of a Method of Lyapunov , 1984, Transp. Sci..

[16]  Georgios K. Ouzounis,et al.  Smart cities of the future , 2012, The European Physical Journal Special Topics.

[17]  Josef Hofbauer,et al.  Evolutionary Games and Population Dynamics , 1998 .

[18]  William H. Sandholm,et al.  Population Games and Deterministic Evolutionary Dynamics , 2015 .

[19]  Jan L.M. Hensen,et al.  State of the art in lighting simulation for building science: a literature review , 2012 .

[20]  宮森 悠.  ライブラリー Annual Energy Outlook 2000 , 2000 .

[21]  Alison Williams,et al.  Lighting Controls in Commercial Buildings , 2012 .

[22]  J. M. Smith,et al.  The Logic of Animal Conflict , 1973, Nature.

[23]  Nicanor Quijano,et al.  Delay Independent Evolutionary Dynamics for Resource Allocation with Asynchronous Distributed Sensors1 , 2012 .

[24]  Andres Pantoja,et al.  Dispatch of distributed generators under local-information constraints , 2014, 2014 American Control Conference.

[25]  Emilio Frazzoli,et al.  Distributed robust adaptive equilibrium computation for generalized convex games , 2015, Autom..

[26]  Nicanor Quijano,et al.  MatSWMM - An open-source toolbox for designing real-time control of urban drainage systems , 2016, Environ. Model. Softw..

[27]  Nicanor Quijano,et al.  The Ideal Free Distribution: Theory and Engineering Application , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[28]  Walid Saad,et al.  Game-Theoretic Methods for the Smart Grid: An Overview of Microgrid Systems, Demand-Side Management, and Smart Grid Communications , 2012, IEEE Signal Processing Magazine.

[29]  Reza Olfati-Saber,et al.  Consensus and Cooperation in Networked Multi-Agent Systems , 2007, Proceedings of the IEEE.

[30]  Narayan B. Mandayam,et al.  Evolutionary game theoretic analysis of distributed denial of service attacks in a wireless network , 2016, 2016 Annual Conference on Information Science and Systems (CISS).

[31]  Alice M. Agogino,et al.  Control of wireless-networked lighting in open-plan offices , 2011 .

[32]  Frank L. Lewis,et al.  Optimal Adaptive Control and Differential Games by Reinforcement Learning Principles , 2012 .

[33]  Nicanor Quijano,et al.  Distributed Population Dynamics: Optimization and Control Applications , 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[34]  N. Britton.  Essential Mathematical Biology , 2004 .

[35]  Jason R. Marden,et al.  A Model-Free Approach to Wind Farm Control Using Game Theoretic Methods , 2013, IEEE Transactions on Control Systems Technology.

[36]  Daniel Pérez Palomar,et al.  A tutorial on decomposition methods for network utility maximization , 2006, IEEE Journal on Selected Areas in Communications.

[37]  L. Blume.  The Statistical Mechanics of Strategic Interaction , 1993 .

[38]  Walid Saad,et al.  Game Theoretic Methods for the Smart Grid , 2012, ArXiv.

[39]  Jean Ponce,et al.  Computer Vision: A Modern Approach , 2002 .

[40]  M. Nowak,et al.  Evolutionary games and spatial chaos , 1992, Nature.

[41]  Jason R. Marden.  State based potential games , 2012, Autom..

[42]  Diodato Ferraioli,et al.  Logit dynamics: a model for bounded rationality , 2013, SECO.

[43]  Seung-Il Moon,et al.  Economic scheduling of distributed generators in a microgrid considering various constraints , 2009, 2009 IEEE Power & Energy Society General Meeting.

[44]  Gürdal Arslan,et al.  Distributed convergence to Nash equilibria with local utility measurements , 2004, 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601).

[45]  Nicanor Quijano,et al.  Decentralized Control for Urban Drainage Systems via population dynamics: Bogotá case study , 2015, 2015 European Control Conference (ECC).

[46]  Toshihide Ibaraki,et al.  Resource allocation problems - algorithmic approaches , 1988, MIT Press series in the foundations of computing.

[47]  Nicanor Quijano,et al.  Modeling and real-time control of urban drainage systems: A review☆ , 2015 .

[48]  Roland K. Price,et al.  Urban Hydroinformatics: Data, Models and Decision Support for Integrated Urban Water Management , 2012 .

[49]  Samson Lasaulce,et al.  Game Theory and Learning for Wireless Networks: Fundamentals and Applications , 2011 .

[50]  D. Goldsman.  Operations Research Models and Methods , 2003 .

[51]  Allen J. Wood,et al.  Power Generation, Operation, and Control , 1984 .

[52]  Jason R. Marden,et al.  Game Theory and Distributed Control , 2015 .

[53]  Anastasios I. Dounis,et al.  Advanced control systems engineering for energy and comfort management in a building environment--A review , 2009 .

[54]  J M Smith,et al.  Evolution and the theory of games , 1976 .

[55]  Lacra Pavel,et al.  Game Theory for Control of Optical Networks , 2012 .

[56]  Asuman E. Ozdaglar,et al.  Network Games: Theory, Models, and Dynamics , 2011, Network Games: Theory, Models, and Dynamics.

[57]  Günther Palm,et al.  Evolutionary stable strategies and game dynamics for n-person games , 1984 .

[58]  Jason R. Marden,et al.  Decoupling Coupled Constraints Through Utility Design , 2014, IEEE Transactions on Automatic Control.

[59]  Nicanor Quijano,et al.  Shahshahani gradient-like extremum seeking , 2015, Autom..

[60]  William H. Sandholm,et al.  The projection dynamic and the geometry of population games , 2008, Games Econ. Behav..

[61]  Volker Stix,et al.  Approximating the maximum weight clique using replicator dynamics , 2000, IEEE Trans. Neural Networks Learn. Syst..

[62]  Jiming Chen,et al.  Building-Environment Control With Wireless Sensor and Actuator Networks: Centralized Versus Distributed , 2010, IEEE Transactions on Industrial Electronics.

[63]  Walid Saad,et al.  A Game-Theoretic Approach to Energy Trading in the Smart Grid , 2013, IEEE Transactions on Smart Grid.

[64]  Eitan Altman,et al.  Evolutionary Games in Wireless Networks , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[65]  Andres Pantoja,et al.  A Population Dynamics Approach for the Dispatch of Distributed Generators , 2011, IEEE Transactions on Industrial Electronics.

[66]  Nicanor Quijano,et al.  Population Games Methods for Distributed Control of Microgrids , 2015, IEEE Transactions on Smart Grid.

[67]  Jason R. Marden,et al.  Designing Games for Distributed Optimization , 2013, IEEE J. Sel. Top. Signal Process..

[68]  V. T. Chow.  Open-channel hydraulics , 1959 .

[69]  José Ramón Gil-García,et al.  Understanding Smart Cities: An Integrative Framework , 2012, HICSS.

[70]  Nicanor Quijano,et al.  Dynamic Population Games for Optimal Dispatch on Hierarchical Microgrid Control , 2014, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[71]  Joaquín Sánchez-Soriano,et al.  An Overview on Game Theory Applications to Engineering , 2013, IGTR.

[72]  Ross Cressman,et al.  The ideal free distribution: a review and synthesis of the game-theoretic perspective. , 2008, Theoretical population biology.

[73]  Andres Pantoja,et al.  Distributed optimization using population dynamics with a local replicator equation , 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).