The influence of rewards on (sub-)optimal interleaving
| Autor: | Janssen, C.P., Everaert, E., Hendriksen, Heleen, Mensing, Ghislaine, Tigchelaar, Laura, Nunner, H., Leerstoel Kenemans, LS Psycholinguistiek, Leerstoel Buskens, Helmholtz Institute, Experimental Psychology (onderzoeksprogramma PF), Afd Psychologische functieleer, Social Networks, Solidarity and Inequality |
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| Přispěvatelé: | Neurology, Amsterdam Neuroscience - Neurodegeneration |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Male
Interleaving Computer science Economics Social Sciences Variation (game tree) 0302 clinical medicine Learning and Memory Task Performance and Analysis Human Performance Psychology multitasking Foraging reward Multidisciplinary Animal Behavior Simulation and Modeling 05 social sciences Multitasking Behavior cognitive model Medicine Female Research Article Adult Mathematical optimization Experimental Economics Science Models Psychological Research and Analysis Methods 050105 experimental psychology 03 medical and health sciences Young Adult Human Learning Humans Learning 0501 psychology and cognitive sciences Computer Simulation Structure (mathematical logic) Behavior Cognitive Psychology Biology and Life Sciences payoff functions cognitive modeling optimality discretionary task interleaving efficiency Cognitive Science Zoology 030217 neurology & neurosurgery Neuroscience |
| Zdroj: | PLoS ONE, 14(3). Public Library of Science PLoS One, 14(3). Public Library of Science PLoS ONE Janssen, C P, Everaert, E, Hendriksen, H M A, Mensing, G L, Tigchelaar, L J & Nunner, H 2019, ' The influence of rewards on (sub-)optimal interleaving ', PLoS ONE, vol. 14, no. 3, pp. e0214027 . https://doi.org/10.1371/journal.pone.0214027 PLoS ONE, Vol 14, Iss 3, p e0214027 (2019) |
| ISSN: | 1932-6203 |
| DOI: | 10.1371/journal.pone.0214027 |
| Popis: | We investigate how the rewards of individual tasks dictate a priori how easy it is to interleave two discrete tasks efficiently, and whether people then interleave efficiently. Previous research found that people vary in their ability to interleave efficiently. Less attention has been given to whether it was realistic to expect efficient interleaving, given the reward rate of each of the involved tasks. Using a simulation model, we demonstrate how the rewards of individual tasks lead to different dual-task interleaving scenarios. We identify three unique dual-task scenarios. In easy scenarios, many strategies for time division between tasks can achieve optimal performance. This gives great opportunity to optimize performance, but also leads to variation in the applied strategies due to a lack of pressure to settle on a small set of optimal strategies. In difficult scenarios, the optimal strategy is hard to identify, therefore giving little opportunity to optimize. Finally, constrained scenarios have a well-defined prediction of the optimal strategy. It gives a narrow prediction, which limits the options to achieve optimal scores, yet given the structure people are able to optimize their strategies. These scenarios are therefore best to test people's general capability of optimizing interleaving. We report three empirical studies that test these hypotheses. In each study, participants interleave between two identical discrete tasks, that differ only in the underlying reward functions and the combined result (easy, difficult, or constrained scenario). Empirical results match the theoretical pattern as predicted by simulation models. Implications for theory and practice are discussed. |
| Databáze: | OpenAIRE |
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