, which may not be good examples of self-organization as discussed in this article.) and evolution by variation and natural selection (\citealp{Sayama_1999}; \citealp{Sayama_2004}; \citealp{Salzberg_2004}; \citealp{Suzuki_2006}; \citealp{Oros_2007}; \citealp{Oros_2009}). Similarly, partial differential equations (PDEs), a continuous-space counterpart of cellular automata, have even longer history of demonstrating self-organizing behaviors in computational media (\citealp{TURING_1990}; \citealp{prigogine1971}; \citealp{Field_1974}; \citealp{Pearson_1993}).
//overlap with artificial societies and now computational social science, also with computational biology
//Self-replication can be seen as a special case of self-organization, as a replicator has to conserve and duplicate its organization by itself. Examples from von Neumann to Langton have been already mentioned, although there have been several more (
Sipper, 1998).
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}.
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}.