David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
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 thesis I propose a methodology to aid engineers in the design and control of complex systems. This is based on the description of systems as self-organizing. Starting from the agent metaphor, the methodology proposes a conceptual framework and a series of steps to follow to find proper mechanisms that will promote elements to find solutions by actively interacting among themselves. The main premise of the methodology claims that reducing the “friction” of interactions between elements 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 practical 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 improving communication within self-organizing bureaucracies are advanced, 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 discussed. Philosophical implications of the conceptual framework are also put forward.
|Keywords||No keywords specified (fix it)|
No categories specified
(categorize this paper)
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library||
References found in this work BETA
No references found.
Citations of this work BETA
Carlos Gershenson & David A. Rosenblueth (2012). Self‐Organizing Traffic Lights at Multiple‐Street Intersections. Complexity 17 (4):23-39.
Carlos Gershenson (2011). The Sigma Profile: A Formal Tool to Study Organization and its Evolution at Multiple Scales. Complexity 16 (5):37-44.
Carlos Gershenson & Nelson Fernandez (2012). Complexity and Information: Measuring Emergence, Self‐Organization, and Homeostasis at Multiple Scales. Complexity 18 (2):29-44.
Similar books and articles
Kara Vander Linden (2006). A Grounded Approach to the Study of Complex Systems. World Futures 62 (7):491 – 497.
Robert C. Richardson (2001). Complexity, Self-Organization and Selection. Biology and Philosophy 16 (5):653-682.
Réjane Bernier (1986). Self-Organizing Potential and Morphogenetic Potential (Comparing Current Embryological and Atlan's Views). Acta Biotheoretica 35 (3).
J. Scott Jordan & Marcello Ghin (2007). The Role of Control in a Science of Consciousness: Causality, Regulation and Self- Sustainment. Journal of Consciousness Studies 14 (s 1-2):177-197.
Gary Metcalf (2003). Learning to Design Systems. World Futures 59 (1):21 – 36.
Michael J. Behe (2000). Self-Organization and Irreducibly Complex Systems: A Reply to Shanks and Joplin. Philosophy of Science 67 (1):155-162.
Ulrich Krohs (2008). Co-Designing Social Systems by Designing Technical Artifacts. In Pieter E. Vermaas, Peter Kroes, Andrew Light & Steven A. Moore (eds.), Philosophy and Design: From Engineering to Architecture. Springer.
Sorry, there are not enough data points to plot this chart.
Added to index2009-01-28
Total downloads1 ( #447,907 of 1,102,629 )
Recent downloads (6 months)1 ( #298,160 of 1,102,629 )
How can I increase my downloads?