//Tom Schelling, James Sakoda's work (1970's) on self-organization of agent-based social models.
//briefly mention BA model
//overlap with artificial societies and now computational social science, also with computational biology

Hard ALife

Robots are life-like artefacts when they show the ability to sense and purposely act in their environment. From Braintenberg's vehicles \citep*{Braitenberg:1986} or W. Grey Walter's tortoises \citep{walter1950,walter1951machine}, the hard way of building artificial life exploited the rich dynamics underlying the interaction between a robot and its environment, so that even simple mechanisms and behavioural rules can confer life-like attributes to seemingly dumb machines. Simple rules do not allow to go farther beyond simple life-like behaviour, however. Higher complexity can be attained either by adding rules to the robot, or by adding robots to a system that, through interaction and self-organisation, can present higher cognitive abilities, from adaptive responses to decision making. 
Although self-organisation with robots does not forcedly require many interacting robots, but rather a large number of interactions (see for instance the seminal study on puck clustering \citep{Beckers_2000}, which could be run with a single robot), self-organising robots usually come in pretty large numbers \citep{Rubenstein_2014}
Aggregation of objects or self-aggregation of robots has been tackled through self-organisation inspired by behaviour observed in living systems, such as cockroaches or bees \citep{Garnier2008,Kernbach2009} or designed through automatic methods like artificial evolution \citep{Dorigo_2004,Francesca2014}
The movement of groups of robots can also be self-organised, in order to coordinate the direction of motion and collectively avoid obstacles \cite{Baldassarre_2007,Trianni2006,Turgut_2008}.
Self-organisation is also at the basis of collective decision making in groups of robots, whereby positive feedback from recruitment processes and negative feedback from cross-inhibition contribute to shape the outcome of a decision process \cite{Reina_2018,Valentini_2015,Scheidler_2016,Garnier_2009,Garnier_2013,Kernbach_2009,Francesca_2014,Valentini2017}.
Self-assembly (Whitesides and Grzybowski, 2002) can also be seen as a form of self-organization. There have been several examples in hard ALife of self-assembling or self-reconfigurating robots (Murata et al., 1994Holland and Melhuish, 1999Zykov et al., 2005Dorigo et al., 2006Støy and Nagpal, 2007Ampatzis et al., 2009Rubenstein et al., 2014Werfel et al., 2014).

Wet ALife

Almost all of protocell research involves self-organization, as interactions between molecules that produce membranes, metabolism, or can store information are studied \citep{Protocells2008}

Living Technology

Living technology has been defined as technology which is based on features of living systems \citep{Bedau2009}, such as robustness, adaptability, and self-organization (which can include self-reconfiguration, self-healing, self-management, self-assembly... often named self-* in the context of autonomic computing \citep{Poslad2009}).
Self-organization has been used directly in living technology in a variety of domains \citep{Bedau2013IntroductionLT}, from protocells \citep{Rasmussen2008} to cities \citep*{Gershenson:2013}, and also several methodologies that use self-organization have been proposed in engineering \citep*{Frei:2011}.