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From individual to collective foraging and their interplay: Efficiently balancing trade-offs in search processes

Abstract

Search is a fundamental process that illustrates adaptive, goal-directed behavior across multiple scales and contexts: from organisms foraging for food independently or collectively, to networked teams searching for solutions to a problem. Efficient search in an environment or a problem-space requires managing a primary trade-off between exploiting available options, resources, or information and exploring for more. In collaboration with other co-authors, I present experimental and modeling work on how individuals and groups can balance this and other related trade-offs to search efficiently under different constraints, and the interplay between individual and group search trade-offs and behavior.

Using a virtual game environment with ecologically-valid constraints, I show that individual humans can efficiently search a previously unknown environment by balancing explorative and exploitative search modes and flexibly adapting this balance based on their task and cognitive constraints (Chapter 2). However, as part of a group, individuals are faced with another essential trade-off: whether to use social information to find resources or search independently. Using an agent-based model of collective foraging, I show that selective use of social information and high levels of independent, explorative search can allow groups to simultaneously take advantage of collective information while maintaining exploration for new resources (Chapter 3). Further, I show that groups may not always evolve to be composed of explorers that maximize a group's efficiency and that competition for resources can result in less efficient groups composed of both explorers and exploiters. I further demonstrate how simple heuristics like area-restricted search can benefit explorers and maximize both individual and group search efficiencies (Chapter 4). Finally, a group's ability to search for resources or solutions over a problem-space can also be affected by patterns of social interactions between individuals. By simulating central-place foraging in early humans, I show that their movement patterns could have led them to interact in ways that created social networks efficient at exchanging information and balancing collective exploration and exploitation of solutions (Chapter 5). Taken together, these results suggest that efficient search in individuals and groups is driven by an adaptive balance between exploration and exploitation, which is further affected by their physical and social environments. It also sheds light on the interplay between individual and collective search that has implications for topics ranging from decision-making, animal foraging, organizational learning to cultural evolution.

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