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A tunable algorithm for collective decision-making by ant colonies

A tunable algorithm for collective decision-making by ant colonies. Stephen Pratt Department of Ecology and Evolutionary Biology Princeton University David J.T. Sumpter Department of Zoology Oxford University. A. B. C. Do colonies trade off the speed and accuracy of decision-making?.

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A tunable algorithm for collective decision-making by ant colonies

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  1. A tunable algorithm for collectivedecision-making by ant colonies Stephen Pratt Department of Ecology and Evolutionary Biology Princeton University David J.T. Sumpter Department of Zoology Oxford University

  2. A B C

  3. Do colonies trade off the speed and accuracy of decision-making? Unforced emigration Forced emigration

  4. In forced emigrations, decisions are faster… Unforced emigration Forced emigration 10 Time until completion (hours) Wilcoxon test, P < 0.001 5 0

  5. In forced emigrations, decisions are faster… Unforced emigration Forced emigration 10 Time until completion (hours) Wilcoxon test, P < 0.001 5 0 …but less accurate 10 8 Number of colonies Wilcoxon test, P < 0.05 6 4 2 0 0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0 Proportion of colony in good nest

  6. Better nests experience more recruitmentand faster population growth

  7. Ants start recruitment sooner at better nests

  8. Tandem run

  9. Transport

  10. Emigration has two phases

  11. Tandem run or transport?

  12. Quorum rule: probability of transport increases with site population

  13. Decision algorithm used by active ants

  14. Searchers: Assessors: Recruiters: Passive ants: Recruitment decision model

  15. Quorum rule amplifies difference in recruitment strength

  16. Summary of individual decision rules • Quality-dependent recruitment latency • Faster population growth at better sites • Investment of time to gain information • Quorum rule for start of transport • Amplifier of recruitment rate differences • Error check on individual behavior

  17. Full agent-based model of individual rules

  18. Speed/accuracy tradeoff Speed of emigration Proportion in good nest 20 20 Quorum size 0 0 1 600 1 600 Recruitment latency (min) 0 0.55 1.0 500 min

  19. Investigation of individual behavior underlying tradeoff Unforced emigrations Forced emigrations Good nests Mediocre nests

  20. Ants in forced emigrationsstart recruitment faster

  21. ANOVA: p < 0.0001 Ants in forced emigrationsuse lower quorrum

  22. Acknowledgements Association for the Study of Animal Behaviour Pew Charitable Trusts Human Frontiers Science Program

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