title: Approximating optimal behavioural strategies down to rules-of-thumb: energy reserve changes in pairs of social foragers.
abstract: Functional explanations of behaviour often propose optimal strategies for organisms to follow. These 'best' strategies could be difficult to perform given biological constraints such as neural architecture and physiological constraints. Instead, simple heuristics or 'rules-of-thumb' that approximate these optimal strategies may instead be performed. From a modelling perspective, rules-of-thumb are also useful tools for considering how group behaviour is shaped by the behaviours of individuals. Using simple rules-of-thumb reduces the complexity of these models, but care needs to be taken to use rules that are biologically relevant. Here, we investigate the similarity between the outputs of a two-player dynamic foraging game (which generated optimal but complex solutions) and a computational simulation of the behaviours of the two members of a foraging pair, who instead followed a rule-of-thumb approximation of the game's output. The original game generated complex results, and we demonstrate here that the simulations following the much-simplified rules-of-thumb also generate complex results, suggesting that the rule-of-thumb was sufficient to make some of the model outcomes unpredictable. There was some agreement between both modelling techniques, but some differences arose - particularly when pair members were not identical in how they gained and lost energy. We argue that exploring how rules-of-thumb perform in comparison to their optimal counterparts is an important exercise for biologically validating the output of agent-based models of group behaviour.
authors.affiliation: Centre for Behavioural Biology, University of Bristol, School of Veterinary Science, Langford, Bristol, United Kingdom. sean.rands@bristol.ac.uk
authors.forename: Sean A
authors.initials: SA
authors.lastname: Rands
mesh_terms: D000818:Animals; D004734:Energy Metabolism / Q000502:physiology*; D005247:Feeding Behavior / Q000502:physiology*; D008954:Models, Biological; D012919:Social Behavior