Emergent Field-Driven Robot Swarm States

Social learning in swarm robotics

“…Indeed, a swarm of robots is a complex system by definition, involving individuals whose interactions are difficult to model (e.g. because of the complexity of physical interactions between robots [ 8 , 13 ]). Machine learning—in particular, reinforcement learning methods inspired by natural evolution [ 14 – 16 ]—can automate the design of individual behavioural strategies, provided that it is possible to measure the performance of the swarm on the desired task (e.g.…”

Online Group Dynamics Reveal New Gel Science

“…Theories of aggregation have had a successful history in physics, chemistry and beyond [13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29]. Understandably, most models and analyses in physical and chemical systems have considered constant size populations of N identical objects in a constant volume space.…”

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A better understanding of how support evolves online for undesirable behaviors such as extremism and hate, could help mitigate future harms [1][2][3][4][5][6][7][8][9][10][11][12]. Here we show how the highly irregular growth curves of groups supporting two high-profile extremism movements, can be accurately described if we generalize existing gelation models to account for the facts that the number of potential recruits is timedependent and humans are heterogeneous [13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29]. This leads to a novel generalized Burgers equation that describes these groups' temporal evolution, and predicts a critical influx rate for potential recruits beyond which such groups will not form.

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Active Phases for Particles on Resource Landscapes

“…Active matter exhibits self-mobility [1][2][3], which can appear in biological [4,5], social [6,7], robotic [8,9], and soft matter systems [10,11]. For active matter composed of particles, the motility can be modeled as a motor force providing run-and-tumble or driven diffusive propulsion [1][2][3], and additional dynamics can be included which induce different types of flocking behaviors [12,13].…”

“…Such situations can arise in time dependent environments [7,24], particles coupled to excitable media [25], and colloids on feedback substrates [26]. Recently, Wang et al [9] introduced an ecologyinspired active matter system of robots interacting with a resource substrate where the robots consume the resources and are attracted to regions with the highest resource concentration. This system exhibited numerous phases such as crystalline, liquid, glass, and jammed states.…”