Collective decision-making

Groups making decisions may need to integrate information from different individual sources, evaluate it, and reach consensus on an action. Temnothorax ant colonies need to regularly choose and move to new nest sites, and may modulate the decision process based on urgency, collect information even before it becomes relevant, flexibly change decisions even during the process of implementation, and can serve as a model surprisingly closely resembling groups of neurons making decisions in the brain.

choosing a new nest

Presence of other colonies, pheromone marks, or dead ants are taken into account in nest site choices (and all avoided); a large number of traits of nest sites are evaluated, including size and number and width of entrances.

Franks NR, Dornhaus A, Hitchcock G, Guillem R, Hooper J, Webb C 2007 ‘Avoidance of conspecific colonies during nest choice by ants’ Animal Behaviour 73: 525-534 - pdf - if emigrating in the presence of another conspecific colony, ant colonies chose the nest cavity furthest away from it; unless the two colonies fused (with or without casualties); pheromone marks around nests play a role

Franks, N R, Dornhaus, A, Best, C S, Jones, E L 2006 ‘Decision-making by small and large house-hunting ant colonies: one size fits all’, Animal Behaviour 72: 611-616 - pdf - colonies of any size like large nests, perhaps because they grow into them; larger colonies have more scouts and discover more nests, but then use a higher quorum threshold and more reverse tandem runs to recruit transporters

Franks, N R, Dornhaus, A, Metherell, B G, Nelson, T R, Lanfear, S A J, Symes, W 2006 ‘Not everything that counts can be counted: Ants use multiple metrics for a single nest trait’, Proceedings of the Royal Society: Biological Sciences 273: 165-169 - pdf - ants use light level in the nest to help select nests with fewer, narrower entrances, but other metrics are likely also used; no evidence for strict ‘counting’

Franks, N R, Hooper, J, Webb, C, Dornhaus, A 2005 ‘Tomb evaders: house-hunting hygiene in ants’, Biology Letters 1: 190-192 - pdf - ants avoid new nest sites with dead ants in them

Franks, NR, Dornhaus, A 2003 ‘How might individual honeybees measure massive volumes?’, Proceedings B: Biology Letters 270 (Supplement 2): 181-182 - pdf - conceptual paper suggesting that honey bees could use a Buffon’s-Needle-like algorithm to estimate internal area (as ants do) and add 3-dimensional free diameter measurements to estimate volume of a potential nest cavity

Arriving at consensus

The decision-making process in colony emigrations of Temnothorax ants is generally well-studied (see also other publications by NR Franks and S Pratt and others).

Key general contributions here are showing the similarity to known neural decision-making networks in the brain, and how quorum thresholds can modulate between speed and accuracy of decisions.

For ants, we demonstrate learning of information that will only later be relevant (latent learning, and ability to move unprompted in response to opportunity) and flexibility during the decision (changing their collective mind mid-stream).

Dornhaus, A, Franks, NR, Hawkins, RM, Shere, HNS 2004 ‘Ants move to improve – colonies of Leptothorax albipennis emigrate whenever they find a superior nest site’, Animal Behaviour 67: 959-963 - pdf - ants can emigrate from an intact nest to a preferred one, but it takes long and they use a high quorum threshold

Franks NR, Hooper JW, Dornhaus A, Aukett PJ, Hayward AL, Berghoff S 2007 ‘Reconnaissance and latent learning in ants’, Proceedings of the Royal Society: Biological Sciences 274: 1505-1509 - pdf - ants learn about nest properties even before they need a new nest, and remember this information when the need arises later

Dornhaus A, Franks NR 2006 ‘Colony size affects collective decision-making in the ant Temnothorax albipennis’, Insectes sociaux 53: 420-427 - pdf - ants adjust their individual-level behavior to their colony size; colony size effects are not just emergent from higher worker number. It is likely that quorums are set as relative to colony size in the original nest. Learning may have bigger effects in small colonies.

Franks, NR, Dornhaus, A, Fitzsimmons, JP, Stevens, M, 2003, ‘Speed vs Accuracy in Collective Decision-Making’, Proceedings of the Royal Society: Biological Sciences 270: 2457-2463 - pdf - when time is of the essence, ants use a lower quorum threshold, i.e. rely on fewer other individuals and agreement in the group; as a result, collective decisions become faster and less accurate.

Franks NR, Hooper JW, Gumn M, Bridger TH, Marshall JAR, Groß R, Dornhaus A 2007 ‘Moving targets: collective decisions and flexible choices in house-hunting ants’ Swarm Intelligence 1: 81-94 - pdf - ants

Planque R, Dornhaus A, Franks NR, Kovacs T, Marshall JAR 2007 ‘Weighting waiting in collective decision-making’ Behavioral Ecology and Sociobiology 61: 347-356 - pdf - data re-analysis and model show that ants, in collective emigration decisions, are flexible early on and grow more committed (and inflexible) over time, which is an effective strategy

Marshall JAR, Bogacz R, Dornhaus A, Planque R, Kovacs T, Franks NR, 2009 ‘On optimal decision-making in brains and social insect colonies’ Journal of The Royal Society Interface 6: 1065-1074 - pdf -

Marshall JAR, Bogacz R, Planqué R, Dornhaus A, Kovacs T, Franks NR 2011 ‘On optimal decision making in brains and social insect colonies’, in: Seth et al. (eds.) Modelling Natural Action Selection. Cambridge University Press - pdf -

Marshall JAR, Dornhaus A, Franks NR, Kovacs T 2006 ‘Noise, cost and speed-accuracy trade-offs: decision making in decentralised systems’, Journal of The Royal Society Interface 3: 243-254 - pdf -

Franks NR, Dornhaus A, Marshall JAR, Deuchaume-Moncharmont F-X, 2009. ‘The dawn of a golden age in mathematical insect sociobiology’. In: Eds. J. Fewell & J. Gadau, Organization of Insect Societies, Harvard University Press [invited chapter in edited book] - pdf -

Marshall JAR, Kovacs T, Dornhaus AR, et al 2003 ‘Simulating the evolution of ant behaviour in evaluating nest sites’, Lecture Notes in Artificial Intelligence 2801: 643-650 2003 - pdf -