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We study a minimal cognitive flocking model, which assumes that the movingentities navigate using exclusively the available instantaneous visualinformation. The model consists of active particles, with no memory, thatinteract by a short-ranged, position-based, attractive force that acts inside avision cone (VC) and lack velocity-velocity alignment. We show that this activesystem can exhibit -- due to the VC that breaks Newton's third law -- variouscomplex, large-scale, self-organized patterns. Depending on parameter values,we observe the emergence of aggregates or milling-like patterns, the formationof moving -- locally polar -- files with particles at the front of thesestructures acting as effective leaders, and the self-organization of particlesinto macroscopic nematic structures leading to long-ranged nematic order.Combining simulations and non-linear field equations, we show thatposition-based active models, as the one analyzed here, represent a new classof active systems fundamentally different from other active systems, includingvelocity-alignment-based flocking systems. The reported results are of primeimportance in the study, interpretation, and modeling of collective motionpatterns in living and non-living active systems.

Large-scales patterns in a minimal cognitive flocking model: incidental leaders, nematic patterns, and aggregates