How do  groups of small brained (or no brained) organisms solve complex optimisation problems?

Some of the most powerful and flexible optimisation algorithms to be developed in recent years have been inspired by natural systems: these include genetic algorithms, artificial neural networks and ant colony optimisation algorithms. The natural world represents a gold mine of problem solving algorithms, yet this potential is largely untapped, primarily because biologists have yet to understand the behavioural mechanisms underlying problem solving in many systems. We aim to fill this knowledge gap by dissecting the behaviours that allow ant colonies, bee hives, and slime mould amoebas to collectively make ‘smart’ decisions. 

At the moment, we have three funded projects investigating collective behaviour and swarm intelligence.

1.  Bio-inspired solutions for protecting critical infrastructure systems (Funded by the Branco Weiss- Society in Science Fellowship)

2. Managing risk in supply chains using bio-inspired algorithms (Funded by the Australian Research Council)

3. Dynamic foraging in bees, ants and slime moulds (Funded by the Australian Research Council)

For more info, see:

Latty, T and Beekman, M. Keeping track of changes: foraging performance of ant colonies in dynamic environments. 2013 Animal Behaviour, in press.

  Reid, C. R., Latty, T., & Beekman, M. 2013. Making a trail: informed Argentine ants lead colony to the best food by U-turning coupled with enhanced pheromone laying. Animal Behaviour, in press


Reid, C. R., Beekman, M., Latty, T., & Dussutour, A. 2013. Amoeboid organism uses extracellular secretions to make smart foraging decisions. Behavioral Ecology24: 4, 812-818.

 Reid, C. R., Latty, T., Dussutour, A. & Beekman, M. 2012. Slime mold uses an externalized spatial “memory” to navigate in complex environments. Proceedings of the National Academy of Sciences109, 17490-17494

Granovskiy,B, Latty,T; Duncan,M; Sumpter, D J.T,  Beekman, M 2012. How dancing honey bees keep track of changes: the role of inspector bees. Behavioural Ecology,23, 588-59

 Latty, T, Ramsch, K, Ito,K, Nakagaki,T,  Sumpter, DJT,  Middendorf, M, and Beekman,M.2011 Structure and formation of ant transportation networks. Proceedings of the royal society Interface. 8, 1298-1306

A colony of argentine ants have found the shortest path between there three nests.