Design and Control of Self-Organizing Systems Carlos Gershenson
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Design and Control of Self-organizing Systems Carlos Gershenson New England Complex Systems Institute and Vrije Universiteit Brussel Mexico City Boston Vic¸osa Madrid Cuernavaca Beijing CopIt ArXives 2007 CopIt ArXives Mexico City Boston Vic¸osa Madrid Cuernavaca Beijing Copyright 2007 by Carlos Gershenson Published 2007 by CopIt ArXives All property rights of this publications belong to the author who, however, grants his authorization to the reader to copy, print and distribute his work freely, in part or in full, with the sole conditions that (i) the author name and original title be cited at all times, (iii) the text is not modified or mixed and (iii) the final use of the contents of this publication must be non commercial Failure to meet these conditions will be a violation of the law. Electronically produced using Free Software and in accomplishment with an Open Access spirit for academic publications ABSTRACT Complex systems are usually difficult to design and control. There are several particular methods for coping with complexity, but there is no general approach to build complex systems. In this book I pro- pose a methodology to aid engineers in the design and control of com- plex systems. This is based on the description of systems as self- organizing. Starting from the agent metaphor, the methodology pro- poses a conceptual framework and a series of steps to follow to find proper mechanisms that will promote elements to find solutions by ac- tively interacting among themselves. The main premise of the method- ology claims that reducing the “friction” of interactions between el- ements of a system will result in a higher “satisfaction” of the system, i.e. better performance. A general introduction to complex thinking is given, since designing self-organizing systems requires a non-classical thought, while prac- tical notions of complexity and self-organization are put forward. To illustrate the methodology, I present three case studies. Self-organizing traffic light controllers are proposed and studied with multi-agent simulations, outperforming traditional methods. Methods for im- proving communication within self-organizing bureaucracies are ad- vanced, introducing a simple computational model to illustrate the benefits of self-organization. In the last case study, requirements for self-organizing artifacts in an ambient intelligence scenario are dis- cussed. Philosophical implications of the conceptual framework are also put forward. iii iv Abstract CONTENTS Abstract iii Contentsv List of Figures viii List of Tablesx Acknowledgements xi 1 Introduction1 1.1 Motivation.............................2 1.2 Contributions...........................3 1.3 Outline...............................4 1.3.1 How to Read this Book..................5 1.3.2 How the Book Was Written...............6 2 Complexity9 2.1 Introduction............................ 10 2.2 Classical Thinking......................... 10 2.3 Complexity............................. 11 2.4 Indeterminacy........................... 14 2.5 Nonlinearity and Chaos..................... 17 2.6 Adapting to Complexity..................... 19 2.7 Conclusions............................ 21 3 Self-organization 23 3.1 Introduction............................ 24 3.2 The Representation-Dependent Dynamics of Entropy.... 24 3.3 The Role of the Observer..................... 29 3.4 Ontological Issues......................... 30 3.5 Self-organization: A Practical Notion.............. 32 v vi CONTENTS 3.5.1 Artificial self-organizing systems............ 33 3.5.2 Levels of abstraction................... 34 3.5.3 Coping with the unknown................ 34 3.6 Conclusions............................ 35 4 A General Methodology 37 4.1 Introduction............................ 38 4.2 The Conceptual Framework................... 38 4.3 The Methodology......................... 44 4.3.1 Representation...................... 44 4.3.2 Modeling......................... 46 4.3.3 Simulation......................... 54 4.3.4 Application........................ 54 4.3.5 Evaluation......................... 55 4.3.6 Notes on the Methodology............... 55 4.4 Discussion............................. 57 4.5 Conclusions............................ 60 5 Self-organizing Traffic Lights 63 5.1 Introduction............................ 64 5.2 Applying the Methodology I.................. 65 5.3 Experiments: First Results.................... 71 5.4 Applying the Methodology II.................. 78 5.5 Experiments: Second Results.................. 79 5.6 Applying the Methodology III.................. 84 5.7 Experiments: Third Results................... 86 5.8 Applying the Methodology IV.................. 87 5.9 Discussion............................. 88 5.9.1 Adaptation or optimization?.............. 89 5.9.2 Practicalities........................ 90 5.9.3 Environmental benefits................. 91 5.9.4 Unattended issues.................... 92 5.10 Conclusions............................ 93 6 Self-organizing Bureaucracies 97 6.1 Introduction............................ 98 6.2 Designing Self-organizing Bureaucracies............ 100 6.3 The Role of Communication................... 102 6.3.1 Decision Delays...................... 106 6.4 The Role of Sensors........................ 106 6.5 The Role of Hierarchies...................... 108 CONTENTS vii 6.6 The Role of Context........................ 111 6.7 A Toy Model: Random Agent Networks............ 112 6.7.1 Using self-organization to improve performance... 114 6.7.2 Simulation Results.................... 115 6.7.3 RAN Discussion..................... 117 6.8 Conclusions............................ 125 7 Self-organizing Artifacts 127 7.1 A Scenario............................. 128 7.2 Requirements for self-organizing artifacts........... 129 7.3 Achieving self-organization................... 131 7.4 Learning to communicate.................... 132 7.5 Learning to cooperate....................... 133 7.6 Learning to coordinate...................... 135 7.7 Conclusions............................ 137 8 Conclusions 139 8.1 Achievements........................... 140 8.1.1 Limitations........................ 141 8.2 Future Work............................ 142 8.3 Philosophical Implications.................... 144 8.3.1 Objectivity or Subjectivity? Contextuality!...... 144 8.3.2 The Benefits of Self-organization............ 145 Bibliography 147 Glossary 169 Index 173 LIST OF FIGURES 1.1 Book map.............................5 2.1 Is it a duck, a rabbit, or both?.................. 15 2.2 The same sphere seen from different angles.......... 16 3.1 Entropy increases and decreases for the same system.... 27 4.1 Diagram relating different stages of Methodology....... 44 4.2 Detailed diagram of Methodology................ 58 5.1 Screenshot of a part of the traffic grid.............. 67 5.2 Results for standard methods.................. 73 5.3 Results for self-organizing methods.............. 74 5.4 Full synchronization....................... 77 5.5 Second results for standard methods.............. 80 5.6 Second results for self-organizing methods.......... 81 5.7 Comparison of initial and average number of cars...... 82 5.8 Simulation of the Wetstraat and intersecting streets..... 85 5.9 Wetstraat results.......................... 95 5.10 Potential implementation of sotl-platoon............. 96 6.1 Asynchronous communication................. 104 6.2 Response delay.......................... 105 6.3 Hierarchy represented as a network.............. 110 6.4 Dynamics of a random agent network of N = 25, K = 5 ... 113 6.5 RAN self-organization mechanism............... 114 6.6 Results for N = 15, K = 1..................... 116 6.7 Results for N = 15, K = 2..................... 118 6.8 Results for N = 15, K = 5..................... 119 6.9 Results for N = 15, K = 15.................... 120 6.10 Results for N = 100, K = 1.................... 121 6.11 Results for N = 100, K = 2.................... 122 6.12 Results for N = 100, K = 5.................... 123 viii LIST OF FIGURES ix 6.13 Results for N = 100, K = 100................... 124 LIST OF TABLES 5.1 Parameters of NetLogo simulations............... 72 5.2 Vehicle count per hour, Wetstraat................ 85 5.3 Emissions by idling engines on Wetstraat........... 92 x ACKNOWLEDGEMENTS This book is one of the outcomes of my PhD at the Vrije Universiteit Brus- sel between November 2002 and May 2007. It takes several years to build up a PhD. And it is impossible to do so alone. Along these years, many mentors, colleagues, and friends have influenced my research, formation, and life in different aspects. I am in debt with my promoters, Francis Heylighen, Diederik Aerts, and Bart D’Hooghe, who have shared their knowledge and experience, and whose support has gone well beyond the academic. Collaborations with Johan Bollen, Jan Broekaert, Paul Cilliers, Seung Bae Cools, Atin Das, Bruce Edmonds, Angelica´ Garc´ıa Vega, Stuart Kauff- man, Tom Lenaerts, Carlos de la Mora, Marko Rodriguez, Ilya Shmule- vich, Dan Steinbock, Jen Watkins, and Andy Wuensche have enriched my research. I have learned a lot from interacting with them. Hugues Bersini, Jean-Louis Denebourg, Marco Dorigo, Bernard Man- derick, Gregoire Nicolis, Ann Nowe, Luc Steels, Rene´ Thomas, Jean Paul Van Bendegem, Frank Van Overwalle, and other professors at the VUB and ULB have provided me with great advice and inspiration. Being in Brussels, I had the opportunity to interact with several re- search groups akin to my interests in both VUB and ULB. I am grateful for the discussions and good