@article {Gershenson:2013,
	title = {Living in Living Cities},
	journal = {Artificial Life},
	volume = {In Press},
	year = {2013},
	abstract = {<p>This paper presents and overview of current and potential applications of living technology to urban problems. Living technology can be described as technology that exhibits the core features of living systems. These features can be useful to solve dynamic problems. In particular, urban problems concerning mobility, logistics, telecommunications, governance, safety, sustainability, and society and culture are presented, while solutions involving living technology are reviewed. A methodology for developing living technology is mentioned, while self-organizing traffic lights are used as a case study of the benefits of urban living technology. Finally, the usefulness of describing cities as living systems is discussed.</p>
},
	keywords = {cities, Self-organization, traffic, transport},
	url = {http://arxiv.org/abs/1111.3659},
	author = {Carlos Gershenson}
}
@book {GershensonDCSOS,
	title = {Design and Control of Self-organizing Systems},
	year = {2007},
	note = {http://tinyurl.com/DCSOS2007},
	publisher = {CopIt Arxives},
	organization = {CopIt Arxives},
	address = {Mexico},
	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.},
	keywords = {Complexity Theory, Physics, Self-organization},
	isbn = {978-0-9831172-3-0},
	url = {http://tinyurl.com/DCSOS2007},
	author = {Carlos Gershenson}
}
