title: Pursuit of food versus pursuit of information in a Markovian perception-action loop model of foraging.
abstract: Efficient coding, redundancy reduction, and other information theoretic optimization principles have successfully explained the organization of many biological phenomena, from the physiology of sensory receptive fields to the variability of certain DNA sequence ensembles. Here we examine the hypothesis that behavioral strategies that are optimal for survival must necessarily involve efficient information processing, and ask whether there can be circumstances in which deliberately sacrificing some information can lead to higher utility? To this end, we present an analytically tractable model for a particular instance of a perception-action loop: a creature searching for a randomly moving food source confined to a 1D ring world. The model incorporates the statistical structure of the creature's world, the effects of the creature's actions on that structure, and the creature's strategic decision process. The underlying model takes the form of a Markov process on an infinite dimensional state space. To analyze it we construct an exact coarse graining that reduces the model to a Markov process on a finite number of "information states". This mathematical technique allows us to make quantitative comparisons between the performance of an information-theoretically optimal strategy with other candidate search strategies on a food gathering task. We find that 1. Information optimal search does not necessarily optimize utility (expected food gain). 2. The rank ordering of search strategies by information performance does not predict their ordering by expected food obtained. 3. The relative advantage of different strategies depends on the statistical structure of the environment, in particular the variability of motion of the source. We conclude that there is no simple relationship between information and utility. Even in the absence of information processing costs or bandwidth constraints, behavioral optimality does not imply information efficiency, nor is there a simple tradeoff between the two objectives of gaining information about a food source versus obtaining the food itself. For a wide range of values of the food source's movement parameter, the strategy of collecting the most information possible about the unknown source location carries an ineliminable structural cost, leading to a situation in which a foraging creature could actually choose to be less well-informed while simultaneously being, on average, better fed.
authors.affiliation: Department of Mathematics, Case Western Reserve University, Cleveland, Ohio 44106, USA.
authors.forename: Edward K
authors.initials: EK
authors.lastname: Agarwala
authors.forename: Hillel J
authors.initials: HJ
authors.lastname: Chiel
authors.forename: Peter J
authors.initials: PJ
authors.lastname: Thomas
mesh_terms: D000465:Algorithms; D000818:Animals; D001522:Behavior, Animal / Q000502:physiology; D017753:Ecosystem; D005247:Feeding Behavior / Q000502:physiology*; D057226:Information Seeking Behavior / Q000502:physiology*; D007257:Information Theory; D008390:Markov Chains; D008954:Models, Biological; D009039:Motion Perception / Q000502:physiology; D009068:Movement / Q000502:physiology