@inbook {GershensonALife2018,
	title = {Self-Organization and Artificial Life: A Review},
	booktitle = {The 2018 Conference on Artificial Life: A Hybrid of the European Conference on Artificial Life (ECAL) and the International Conference on the Synthesis and Simulation of Living Systems (ALIFE)},
	year = {2018},
	pages = {510{\textendash}517},
	publisher = {MIT Press},
	organization = {MIT Press},
	address = {Tokyo, Japan},
	abstract = {Self-organization has been an important concept within a number of disciplines, which Artificial Life (ALife) also has heavily utilized since its inception. The term and its implications, however, are often confusing or misinterpreted. In this work, we provide a mini-review of self-organization and its relationship with ALife, aiming at initiating discussions on this important topic with the interested audience. We first articulate some fundamental aspects of self-organization, outline its usage, and review its applications to ALife within its soft, hard, and wet domains. We also provide perspectives for further research.},
	doi = {10.1162/isal_a_00094},
	url = {https://www.mitpressjournals.org/doi/abs/10.1162/isal_a_00094},
	author = {Gershenson, Carlos and Trianni, Vito and Werfel, Justin and Sayama, Hiroki},
	editor = {Takashi Ikegami and Nathaniel Virgo and Olaf Witkowski and Mizuki Oka and Reiji Suzuki and Hiroyuki Iizuka}
}
@unpublished {goel2017self,
	title = {Self-Organization in Traffic Lights: Evolution of Signal Control with Advances in Sensors and Communications},
	year = {2017},
	note = {arXiv:1708.07188},
	url = {https://arxiv.org/abs/1708.07188},
	author = {Goel, Sanjay and Bush, Stephen F and Gershenson, Carlos}
}
@inbook {CortesIWSOS2013,
	title = {Self-organization Promotes the Evolution of Cooperation with Cultural Propagation},
	booktitle = {Self-Organizing Systems},
	series = {Lecture Notes in Computer Science},
	volume = {8221},
	year = {2014},
	pages = {145-150},
	publisher = {Springer},
	organization = {Springer},
	address = {Berlin Heidelberg},
	abstract = {In this paper three computational models for the study of the evolution of cooperation under cultural propagation are studied: Kin Selection, Direct Reciprocity and Indirect Reciprocity. Two analyzes are reported, one comparing their behavior between them and a second one identifying the impact that different parameters have in the model dynamics. The results of these analyzes illustrate how game transitions may occur depending of some parameters within the models and also explain how agents adapt to these transitions by individually choosing their attachment to a cooperative attitude. These parameters regulate how cooperation can self-organize under different circumstances. The emergence of the evolution of cooperation as a result of the agent{\textquoteright}s adapting processes is also discussed.},
	isbn = {978-3-642-54139-1},
	doi = {10.1007/978-3-642-54140-7_13},
	url = {http://dx.doi.org/10.1007/978-3-642-54140-7_13},
	author = {Cort{\'e}s-Berrueco, LuisEnrique and Gershenson, Carlos and Stephens, ChristopherR.},
	editor = {Elmenreich, Wilfried and Dressler, Falko and Loreto, Vittorio}
}
@article {doi:10.1162/artl.2008.14.2.239,
	title = {Self-Organization and Emergence in Life Sciences. Bernard Feltz, Marc Crommelinck, and Philippe Goujon (Eds.). (2006, Synthese Library Vol. 331, Springer.) Hardcover, {\texteuro}139, $179, 360 pages},
	journal = {Artificial Life},
	volume = {14},
	number = {2},
	year = {2008},
	pages = {239-240},
	doi = {10.1162/artl.2008.14.2.239},
	url = {http://www.mitpressjournals.org/doi/abs/10.1162/artl.2008.14.2.239},
	author = {Gershenson, Carlos}
}
@conference {RodriguezEtAl2007,
	title = {Smartocracy: Social Networks for Collective Decision Making},
	booktitle = {Hawaii International Conference on Systems Science (HICSS)},
	year = {2007},
	publisher = {IEEE Computer Society},
	organization = {IEEE Computer Society},
	abstract = {Smartocracy is a social software system for collec- tive decision making. The system is composed of a social network that links individuals to those they trust to make good decisions and a decision network that links individuals to their voted-on solutions. Such networks allow a variety of algorithms to convert the link choices made by individual participants into specific decision outcomes. Simply interpreting the linkages differently (e.g. ignoring trust links, or using them to weight an individual{\textquoteright}s vote) provides a variety of outcomes fit for different decision making scenarios. This paper will discuss the Smartocracy network data structures, the suite of collective decision making algorithms currently supported, and the results of two collective decisions regarding the design of the system.},
	doi = {10.1109/HICSS.2007.484},
	url = {http://tinyurl.com/ybojp8},
	author = {Rodriguez, Marko A. and Steinbock, Daniel J. and Watkins, Jennifer H. and Gershenson, Carlos and Bollen, Johan and Grey, Victor and deGraf, Brad}
}
