Social search (using social information to locate resources) has evolved stably across a wide range of species. The current research systematically investigates dynamical interactions between social search strategies of consumers and clustering of resource environments in simple 2D worlds. Previous work finds that clustering of resources (e.g., information, food) promotes use of social search, and other studies find the corresponding effect that social search leads to increased resource clustering. In Experiment 1 and 2 we replicate these results in simulations by fixing resource distributions and social search respectively at different levels and observing their influence on the other. Our results additionally show an inverse U-shaped trend between the two—as resource clustering increases, so does social search (as expected); however, at very high values of clustering, adaptive benefits of social search decline. Similar trends are obtained when social search is manipulated and resulting resource clustering is analyzed. In Experiment 3, we simulate dynamical systems where both social search and resource clustering are left unconstrained so they can mutually influence one other. These simulations are representative of real-world systems where species can flexibly alter their search strategies in response to the environment (e.g., through learning or evolution) and resource distributions are in turn influenced by consumer behavior. Here, we find that both social search and resource clustering evolve to positive values, indicating that they may be stable states of such systems. Our results have implications across a wide range of search domains—similar dynamics between social search and resource clustering are observed in multidimensional environments of informational and cultural search and simpler 2- and 3-D environments of ecological search.

Many lifeforms are found in patches that other lifeforms forage for and consume. Here we explore how the patchiness of the former and cognition of the latter may emerge through mutual interaction in an agent-based model. We use a simple 2D grid world consisting of two types of agents—plants (prey) and animals (predators). Across three experiments, we investigate how cognition of animals influences patchiness of plants and evolves in response to it. Here, cognition is a probabilistic model with two parameters, one for distance of perception and the other for determinacy versus stochasticity of movement. We found that plant patchiness emerged alongside the evolution of animal cognition. In addition, greater distance of perception reduced patchiness, while greater determinacy of movement increased patchiness. Conversely, greater patchiness of plants led animals to evolve perception across greater distances but also led to evolution of less deterministic foraging. Environmental patchiness and foraging cognition thus appeared to mutually create a stable dynamic interaction leading to a self-regulating system.