00503nas a2200145   4500008004100000245008700041210006900128260003000197300001400227490000800241100001500249700002300264700001900287856005100306       2014                        eng d00aDecoding Road Networks into Ancient Routes: The Case of the Aztec Empire in Mexico0 aDecoding Road Networks into Ancient Routes The Case of the Aztec  aBerlin, GermanybSpringer  a228–2330 v1261 aLugo, Igor1 aGershenson, Carlos1 aGlass, Kristin  uhttp://dx.doi.org/10.1007/978-3-319-03473-7_2000372nas a2200121   4500008004100000245003400041210003300075260002800108100002300136700001900159700002400178856004800202       2014                        eng d00aDolor, placebos y complejidad0 aDolor placebos y complejidad  aMexicobEditorial Alfil1 aGershenson, Carlos1 aRosado, Javier1 aBistre-Cohén, Sara  uhttp://turing.iimas.unam.mx/sos/?q=node/15301910nas a2200109   4500008004100000245005000041210004900091260005500140520155100195100002301746856003101769       2007                        eng d00aDesign and Control of Self-organizing Systems0 aDesign and Control of Selforganizing Systems  aBrussels, BelgiumbVrije Universiteit BrusselcMay3 aComplex 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.1 aGershenson, Carlos  uhttp://cogprints.org/5442/02024nam a2200157   4500008004100000020002200041245005000063210004900113260002600162520156600188653002201754653001201776653002201788100002301810856003301833       2007                        eng d  a978-0-9831172-3-000aDesign and Control of Self-organizing Systems0 aDesign and Control of Selforganizing Systems  aMexicobCopIt Arxives3 aComplex 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.10aComplexity Theory10aPhysics10aSelf-organization1 aGershenson, Carlos  uhttp://tinyurl.com/DCSOS2007