Coevolution in Hide and Seek: Camouflage and Vision

Predator-prey interactions are one of the most common coevolutionary dynamics in Nature. We consider a model of the coevolution of prey appearance and predator vision, where a successful result is visually apparent. While using a neurophysiologically-based model of vision and a rich developmental process for prey patterning, we show that predatorprey coevolution can maintain engagement. Backgrounds with large regional differences generally lead to prey that appear as mixtures of the regions. Finally, we find that engagement between predators and prey is supported by greater background complexity. One of the most visually-striking phenomena in predatorprey coevolution is prey crypsis, the ability of prey to avoid detection by predators. Chameleons and cuttlefish take this behavior to the extreme and physically alter their pigmentation to match their environment, which can even be realized synthetically in robots (Morin et al., 2012). However, prey crypsis is often manifested as static pigmentations, such as stationary Turing patterns (Turing, 1952), that are selected for being advantageous in particular environments. Inspired by Bond and Kamil (2002), where blue jays are used to interactively evolve moth phenotypes, we study the effect of background complexity on the coevolution of prey appearance and predator vision. There is an intimate coevolutionary relationship between predator vision and prey appearance. Visual systems are generally adapted for stimuli that exert selective pressure on the organism, such as food, prey, predators, and mates. Even when visual systems have adapted to attenuate visual signals from their relevant stimuli, there is still the challenge of visual attention. Visual attention can be roughly thought of as a way of prioritizing a visual field based on interest. Improper allocation of visual attention can mean the difference between catching dinner or going home hungry. In this research we study the coevolution of prey appearance and visual attention in predators. Prey appearance is evolved via genetic programming, such as in (Sims, 1991a; Reynolds, 2011). Predator vision is evolved using a neurophysiologically-based model of visual attention (Itti and Koch, 2001). We focus on the effects of environmental complexity on this coevolutionary interaction. Merilaita (2003) shows that greater background complexity can increase prey detection times by predators. In even earlier work on background matching in camouflage, it was suggested that visual complexity may favor color polymorphism, because there will often be many polymorphisms that can achieve similar patterns (Endler, 1984). These and other works focus on camouflage via background matching, but there are alternative forms of camouflage, in particular, disruptive colorations. In contrast to background matching, where an entity attempts to blend in with the background, disruptive and distractive colorations are patterns that attempt to draw the observer away from the pattern. Disruptive colorations have been shown to be an effective tool for camouflage when tested against live predators (Schaefer and Stobbe, 2006; Cuthill et al., 2005). A number of visual properties significant to predator-prey interactions have been identified in these contexts, including background complexity, prey contrast, and object density (Dimitrova and Merilaita, 2010, 2012, 2014). In our model, the capacity for complexity in prey is greatly enhanced by utilizing a developmental mechanism to produce color images of moderate dimensions, as compared to previous work which explores the selective favorability of simple patterns (Dimitrova and Merilaita, 2014) or directly-represented greyscale images (Bond and Kamil, 2002). In previous work, we have explored the coevolution of predators and prey (Ficici and Pollack, 1996), finding that such systems are often subject to pathologies such as convergence to mediocre stable states (Ficici and Pollack, 1998), loss of gradient, incorrect focusing, and relativism (Watson and Pollack, 1996). Within the ecology literature, predator-prey systems are commonly studied, including analytical and computational models as well as empirical studies. However, analytical models of predator-prey systems can quickly become infeasible for study as the number of species increases. Furthermore, analysis of phenomena such as predator preference runs into difficulty when accounting for alternative food sources under ecological dynamics (van (a) T = 1 (b) T = 5 (c) T = 10 (d) T = 15 (e) T = 20 (f) T = 25 (g) Prey in context (h) T = 1 (i) T = 5 (j) T = 10 (k) T = 15 (l) T = 20 (m) T = 25 (n) Prey in context (o) T = 1 (p) T = 5 (q) T = 10 (r) T = 15 (s) T = 20 (t) T = 25 (u) Prey in context Figure 1: Time-series of prey morphogenesis. Baalen et al., 2001; Leeuwen and Brännström, 2013). The pathologies of competitive coevolution can be readily explained in the language of predator-prey systems. Loss of gradient, when one population becomes worse such that it no longer exherts selective pressure on the competing population, or better such that the competing population can no longer maintain engagement. Examples of this would include evolutionary advances in a predator-prey ecosystem where prey can achieve greater escape velocities, leading to diminished returns for predators, and in real ecosystems, probably triggering the predators to seek another food source. Incorrect focusing is when members of one population overspecialize in interactions with specific competitors such that they fail to generalize to other competitive interactions and are prone to extinction. Examples of incorrect focusing are not as common in real ecosystems, where a large number of coevolutionary interactions continually apply selective pressure. In competitive coevolutionary interactions, the quality of an individual is a function of its competitors. This relativism in scoring means that an individual that appears to be more fit to an external observer, may be just as fit as a lower quality individual relative to a given set of competitors. In Nature, this is less of an issue for similar reasons to incorrect focusing, there are continual pressures from many aspects of the ecosystem and environment such that these disambiguations will occur infrequently. Predator-Prey Coevolution When simulating predator-prey coevolution, we use a 2population competitive coevolution model. The prey population consists of a set of genetic programs that encode a generative function for their visual appearance. The predator population consists of a set of numerical weights for a saliency detection algorithm. Prey receive points for not being detected, or causing the predator to incorrectly classify the background as prey. Predators receive points based upon the accuracy of how they perceive the environment. There are a number of ways to compute the fitness in coevolving populations. We focus on pairwise competitions. Sims uses best v. best competitive coevolution (Sims, 1994), where each population competes against the best individual of the competing population. However, best v. best can lead to incorrect focusing and disengagement by assigning greater fitness to individuals that overspecialize in defeating the champion competitor. Tournaments can reduce the number of comparisons from O(N) to O(NlogN), but still represent approximations of a full pairwise competition (Angeline and Pollack, 1993). All v. all competitive coevolution reduces the tendency for focusing, but comes at great computational cost. Nevertheless, we compute the complete payoff matrix via all v. all pairwise competitions to facilitate coevolutionary engagement between all species.