@article {Zapotecatl2017,
	title = {Deliberative Self-Organizing Traffic Lights with Elementary Cellular Automata},
	journal = {Complexity},
	volume = {2017},
	year = {2017},
	pages = {7691370},
	abstract = {Self-organizing traffic lights have shown considerable improvements compared to traditional methods in computer simulations. Self-organizing methods, however, use sophisticated sensors, increasing their cost and limiting their deployment. We propose a novel approach using simple sensors to achieve self-organizing traffic light coordination. The proposed approach involves placing a computer and a presence sensor at the beginning of each block; each such sensor detects a single vehicle. Each computer builds a virtual environment simulating vehicle movement to predict arrivals and departures at the downstream intersection. At each intersection, a computer receives information across a data network from the computers of the neighboring blocks and runs a self-organizing method to control traffic lights. Our simulations showed a superior performance for our approach compared with a traditional method (a green wave) and a similar performance (close to optimal) compared with a self-organizing method using sophisticated sensors but at a lower cost. Moreover, the developed sensing approach exhibited greater robustness against sensor failures.},
	doi = {10.1155/2017/7691370},
	url = {https://doi.org/10.1155/2017/7691370/7691370},
	author = {Zapotecatl, Jorge L. and Rosenblueth, David A. and Gershenson, Carlos}
}
@inbook {LugoGershensonComplex2012,
	title = {Decoding Road Networks into Ancient Routes: The Case of the Aztec Empire in Mexico},
	booktitle = {Proceedings of the Second International Conference on Complex Sciences: Theory and Applications {(COMPLEX 2012)}},
	series = {LNICST},
	volume = {126},
	year = {2014},
	pages = {228{\textendash}233},
	publisher = {Springer},
	organization = {Springer},
	address = {Berlin, Germany},
	doi = {10.1007/978-3-319-03473-7_20},
	url = {http://dx.doi.org/10.1007/978-3-319-03473-7_20},
	author = {Igor Lugo and Carlos Gershenson},
	editor = {Kristin Glass}
}
@inbook {153,
	title = {Dolor, placebos y complejidad},
	booktitle = {Actualidades en el manejo del dolor y cuidados paliativos},
	year = {2014},
	publisher = {Editorial Alfil},
	organization = {Editorial Alfil},
	chapter = {36},
	address = {Mexico},
	author = {Carlos Gershenson and Javier Rosado},
	editor = {Bistre-Coh{\'e}n, Sara}
}
@mastersthesis {GershensonPhD,
	title = {Design and Control of Self-organizing Systems},
	year = {2007},
	month = {May},
	school = {Vrije Universiteit Brussel},
	type = {phd},
	address = {Brussels, Belgium},
	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 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 {\textquoteleft}{\textquoteleft}friction{\textquoteright}{\textquoteright} of interactions between elements of a system will result in a higher {\textquoteleft}{\textquoteleft}satisfaction{\textquoteright}{\textquoteright} 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.},
	url = {http://cogprints.org/5442/},
	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}
}
@conference {GershensonGonzalez2000,
	title = {Dynamic Adjustment of the Motivation Degree in an Action Selection Mechanism},
	booktitle = {Proceedings of {ISA} {\textquoteright}2000},
	year = {2000},
	address = {Wollongong, Australia.},
	abstract = {This paper presents a model for dynamic adjustment of the motivation degree, using a reinforcement learning approach, in an action selection mechanism previously developed by the authors. The learning takes place in the modification of a parameter of the model of combination of internal and external stimuli. Experiments that show the claimed properties are presented, using a VR simulation developed for such purposes. The importance of adaptation by learning in action selection is also discussed.},
	url = {http://uk.arxiv.org/abs/cs.AI/0211038},
	author = {C. Gershenson and P. P. Gonz{\'a}lez}
}
