Optimal cue integration in ants
- Submitting institution
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The University of Sheffield
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 2554
- Type
- D - Journal article
- DOI
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10.1098/rspb.2015.1484
- Title of journal
- Proceedings of the Royal Society B: Biological Sciences
- Article number
- 20151484
- First page
- -
- Volume
- 282
- Issue
- 1816
- ISSN
- 0962-8452
- Open access status
- Out of scope for open access requirements
- Month of publication
- October
- Year of publication
- 2015
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
2
- Research group(s)
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C - Machine Learning
- Citation count
- 59
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work has directly inspired new computational models of optimal information integration in animals (Hoinville & Wehner, PNAS, 2018 (doi.org/10.1073/pnas.1721668115); Sun, eLife, 2020 (doi.org/10.7554/eLife.54026)). It also inspired a collaborative UK-China Ph.D. project (Xuelong Sun) leading to a further publication (doi.org/10.1007/978-3-319-95972-6_49) and follow-on grants (EP/S030964/1). Significance is demonstrated through coverage in reviews in insect neuroscience (Knaden, Current opinion in neurobiology, 2019 (doi.org/10.1016/j.conb.2018.10.005)) and broader cognition and psychology fields (Randolph, Journal of Experimental Psychology: Animal Learning and Cognition, 2020 (doi.org/10.1037/xan0000227); Foley & Marjoram. Animal cognition, 2017, (doi.org/10.1007/s10071-017-1107-5)).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -