Coevolution of Camouflage

author = "Craig Reynolds",

title = "Coevolution of Camouflage",

booktitle = "ALIFE 2023: Ghost in the Machine: Proceedings of the 2023 Artificial Life Conference",

year = "2023",

editor = "Hiroyuki Iizuka and Keisuke Suzuki and Ryoko Uno and Luisa Damiano and Nadine Spychala and Miguel Aguilera and Eduardo Izquierdo and Reiji Suzuki and Manuel Baltieri",

address = "Sapporo, Japan",

month = "24-28 " # jul,

organization = "The International Society for Artificial Life",

publisher = "MIT Press",

email = "cwr@red3d.com",

keywords = "genetic algorithms, genetic programming, camouflage, coevolution, vision, nature, biology, predator, prey, vision, learning, texture synthesis, simulation",

URL = "

https://arxiv.org/abs/2304.11793",

URL = "

https://doi.org/10.1162/isal_a_00583",

size = "39 MB",

abstract = "Camouflage in nature seems to arise from competition between predator and prey. To survive, predators must find prey, and prey must avoid being found. This work simulates an abstract model of that adversarial relationship. It looks at crypsis through evolving prey camouflage patterns (as colour textures) in competition with evolving predator vision. During their lifetime predators learn to better locate camouflaged prey. The environment for this 2D simulation is provided by a set of photographs, typically of natural scenes. This model is based on two evolving populations, one of prey and another of predators. Mutual conflict between these populations can produce both effective prey camouflage and predators skilled at breaking camouflage. The result is an open source artificial life model to help study camouflage in nature, and the perceptual phenomenon of camouflage more generally.",

notes = "also known as \cite{Reynolds_2023}",