@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}
}
@inbook {Gershenson:2011b,
	title = {Self-organizing urban transportation systems},
	booktitle = {Complexity Theories of Cities Have Come of Age: An Overview with Implications to Urban Planning and Design},
	year = {2012},
	pages = {269-279},
	publisher = {Springer},
	organization = {Springer},
	address = {Berlin Heidelberg},
	abstract = {Urban transportation is a complex phenomenon. Since many agents are constantly interacting in parallel, it is difficult to predict the future state of a transportation system. Because of this, optimization techniques tend to give obsolete solutions, as the problem changes before it can be optimized. An alternative lies in seeking adaptive solutions. This adaptation can be achieved with self-organization. In a self-organizing transportation system, the elements of the system follow local rules to achieve a global solution. Like this, when the problem changes the system can adapt by itself to the new configuration. In this chapter, I will review recent, current, and future work on self-organizing transportation systems. Self-organizing traffic lights have proven to improve traffic flow considerably over traditional methods. In public transportation systems, simple rules are being explored to prevent the "equal headway instability" phenomenon. The methods we have used can be also applied to other urban transportation systems and their generality is discussed.},
	doi = {10.1007/978-3-642-24544-2_15},
	url = {http://arxiv.org/abs/0912.1588},
	author = {Carlos Gershenson},
	editor = {Juval Portugali and Han Meyer and Egbert Stolk and Ekim Tan}
}
@conference {Fernandez:2012,
	title = {Sistemas Din{\'a}micos como Redes Computacionales de Agentes para la evaluaci{\'o}n de sus Propiedades Emergentes.},
	booktitle = {II Simposio Cient{\'{\i}fico y Tecnol{\'o}gico en Computaci{\'o}n SCTC 2012},
	year = {2012},
	address = {Universidad Central de Venezuela},
	author = {Nelson Fern{\'a}ndez and Jos{\'e} Aguilar and Carlos Gershenson and Oswaldo Ter{\'a}n}
}
