Assessment and Choice: An Operant Simulation of Foraging in Patches

Abstract

Pigeons were presented with an operant simulation of two prey patches using concurrent randomratio schedules of reinforcement. An unstable patch offered a higher initial reinforcement probability, which then declined unpredictably to a zero reinforcement probability in each session. A stable patch offered a low but unvarying reinforcement probability. When the reinforcement probability declined to zero in a single step, the birds displayed shorter giving-up times in the unstable patch when the ratio between the initial reinforcement probabilities in the unstable and stable patches was greater and when the combined magnitude of the reinforcement probabilities in the two patches was greater. When the unstable patch declined in two steps, the birds behaved as if their giving-up times were influenced heavily by events encountered during the most recent step of the double-step change. This effect was observed, however, only when the reinforcement probability in that step was .04, not when it was .06. All of these data agree with the predictions of a capture-probability model based on a comparison of the estimated probability of receiving a reinforcer in the current patch with that in alternative patches.

Sure enough: efficient Bayesian learning and choice

“…1976; Luttbeg 1996), but it is clear that both can co-occur (Krakauer and Rodríguez-Gironés 1995). Learning with decision-making is often studied in the context of foraging (Roche et al 1996). Accordingly, as our example dataset, we will refer to a study of bee foraging: floral learning and exploitation (Cnaani et al 2006).…”

“…While the importance of reasoning with uncertainty is generally appreciated, it is most common to model belief using point estimates (Roche et al 1996)—for instance, by estimating an “expected mean reward”—and the most commonly utilised learning models, e.g. the Rescorla Wagner model, treat belief as a point estimate (e.g.…”

The behavioral ecology of brand choice: How and what do consumers maximize?

“…This interpretation assumes significance in view of work that casts foraging itself as operant behavior (Shettleworth, 1988). There is a tradition of research to support this view (e.g., Abarca & Fantino, 1982;Dall, Cuthill, Cook, & Morphet, 1997;Dow & Lea, 1987;Fantino & Preston, 1988;Ito & Fantino, 1986;McCarthy, Voss, & Davison, 1994;Mellgren & Brown, 1988;Roberts, 1993;Roche, Stubbs, & Glanz, 1996;Williams & Fantino, 1994. These studies principally involve choices made by nonhuman animals.…”

The influence of artificial paths and landmarks on the foraging behavior of Norway rats (Rattus norvegicus)

“…Conceptual support for the possibility that path following contributes to foraging efficiency is provided by the observation that because energy (food) often occurs in discrete clumps or "patches" within the environment (MacArthur & Pianka, 1966;Roche, 1996;Roche, Stubbs, & Glanz, 1996;Stephens, 1990;Stephens & Krebs, 1986), achieving a high net rate of energy intake frequently relies, in part, on gathering information about the location of food Thanks to Tammi Nelson and Jason Hesting for their technical assistance. Special thanks to Cynthia Hoffman, for helping to pioneer this approach and for making illustrations of the apparatus, and to Joseph Leffel, for all of his invaluable contributions.…”