Pursuit of food versus pursuit of information in a Markovian perception-action loop model of foraging.

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.

Risk dishabituation: in repeated gambling, risk is reduced following low-probability "surprising" events (wins or losses).

In path-dependent risk taking, like playing a slot machine, the wager on one trial may be affected by the outcome of the preceding trial. Previous studies have shown that a person's risk-taking preferences may change as a result of the preceding trial (win or loss). For example, the "house money effect" suggests that risk taking may increase after a win, whereas the "break even effect" posits that risk taking increases after a loss.