Bayesian decision theory and navigation
| العنوان: | Bayesian decision theory and navigation |
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| المؤلفون: | Xiaoli Chen, Timothy P. McNamara |
| المصدر: | Psychonomic Bulletin & Review. 29:721-752 |
| بيانات النشر: | Springer Science and Business Media LLC, 2021. |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | Bayes estimator, Heading (navigation), Arts and Humanities (miscellaneous), Computer science, Bayesian probability, Prior probability, Developmental and Educational Psychology, Experimental and Cognitive Psychology, Cognition, Spatial memory, Sensory cue, Decision model, Cognitive psychology |
| الوصف: | Spatial navigation is a complex cognitive activity that depends on perception, action, memory, reasoning, and problem-solving. Effective navigation depends on the ability to combine information from multiple spatial cues to estimate one's position and the locations of goals. Spatial cues include landmarks, and other visible features of the environment, and body-based cues generated by self-motion (vestibular, proprioceptive, and efferent information). A number of projects have investigated the extent to which visual cues and body-based cues are combined optimally according to statistical principles. Possible limitations of these investigations are that they have not accounted for navigators' prior experiences with or assumptions about the task environment and have not tested complete decision models. We examine cue combination in spatial navigation from a Bayesian perspective and present the fundamental principles of Bayesian decision theory. We show that a complete Bayesian decision model with an explicit loss function can explain a discrepancy between optimal cue weights and empirical cues weights observed by (Chen et al. Cognitive Psychology, 95, 105-144, 2017) and that the use of informative priors to represent cue bias can explain the incongruity between heading variability and heading direction observed by (Zhao and Warren 2015b, Psychological Science, 26[6], 915-924). We also discuss (Petzschner and Glasauer's , Journal of Neuroscience, 31(47), 17220-17229, 2011) use of priors to explain biases in estimates of linear displacements during visual path integration. We conclude that Bayesian decision theory offers a productive theoretical framework for investigating human spatial navigation and believe that it will lead to a deeper understanding of navigational behaviors. |
| تدمد: | 1531-5320 1069-9384 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8c44815e9227ad4d0d9372267b806a27 https://doi.org/10.3758/s13423-021-01988-9 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....8c44815e9227ad4d0d9372267b806a27 |
| قاعدة البيانات: | OpenAIRE |
Find this article in full text from Springer Verlag. | تدمد: | 15315320 10699384 |
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