Author

E. R. Hunt

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Animal Behavior & Cognition· 4

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Approach:Bayesian inference· 1 Assay:behavioral assay· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

N. R. Franks· 3 shared R. J. Baddeley· 3 shared B. M. Wong· 1 shared B. Mi· 1 shared C. Fernandez· 1 shared J. N. Pruitt· 1 shared N. Pinter-Wollman· 1 shared R. Geremew· 1 shared

Activity by Year

2019-2020 · peak 2/yr

Co-Author Collaboration Network

8 top collaborators · 16 mutual co-author links

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3 shared papersAnimal Behavior & Cognition

N. R. Franks

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Author profile →

4 papers

Recent·Most cited

The Bayesian Superorganism: Collective Probability Estimation in Swarm Systems

E. R. Hunt, N. R. Franks, R. J. Baddeley

The paper develops a Bayesian model to explain collective decision-making in ant colonies, showing how decentralized probability estimation can lead to effective nest site selection.

bioRxiv · Jun 4, 2020Animal Behavior & Cognition

The Bayesian Superorganism: externalised memories facilitate distributed sampling

E. R. Hunt, N. R. Franks, R. J. Baddeley

The paper shows ants use externalized chemical markers to coordinate foraging and develops a Bayesian model to improve sampling efficiency in sparse distributions.

bioRxiv · May 28, 2020 · PreprintAnimal Behavior & Cognition

Optimal foraging and the information theory of gambling

R. J. Baddeley, N. R. Franks, E. R. Hunt

This paper applies information theory and Markov chain Monte Carlo methods to model ant foraging behavior, showing that optimal foraging strategies align with betting strategies from gambling theory.

bioRxiv · Jun 25, 2019Animal Behavior & Cognition

Resting networks and personality predict attack speed in social spiders

E. R. Hunt, B. Mi, R. Geremew, C. Fernandez, B. M. Wong, J. N. Pruitt, N. Pinter-Wollman

The paper examines how resting social network structures and individual boldness traits predict attack speed in social spiders, finding that network position and boldness interact to influence collective predation behavior.

bioRxiv · Jun 18, 2019Animal Behavior & Cognition