Distributed Algorithms for Optimal Decision-Making
The DiODe team are organising a conference on Collective Decision-Making to mark the close of the project. This will take place in Sheffield on May 20th and 21st, and features an extensive line-up of high-profile interdisciplinary speakers.
Further details are available at https://cdmconf.group.shef.ac.uk
T. Bose, F. Bottom, A. Reina & J.A.R.Marshall, (2019) Frequency-Sensitivity and Magnitude-Sensitivity in Decision-Making: Predictions of a Theoretical Model-Based Study. Computational Brain & Behavior (Online First).
In this paper we study how decisions can be affected by varying frequencies and magnitudes of a perceptual stimulus in a simulated binary choice task. As a result we find that reaction time distributions may resemble the periodicity of the external stimulus. The article is fully open access.
Bose, T., Reina, A., Marshall, J. A. R. (2019) Inhibition and Excitation Shape Activity Selection: Effect of Oscillations in a Decision-Making Circuit. Neural Computation 31:870-896.
This paper studies a model animal choosing between different food sources in an ongoing decision-making process. The decision-making circuit regulating the response is implemented via a generic neural hardware motif. Nonlinearities in the circuit influence the behaviour of the model animal. We find the unexpected result that inherent oscillations of neuronal activity may enhance decision-making performance.
The DiODe team are finalists for the inaugural Research Software Engineering Prize at the University of Sheffield, for their software MuMoT: Multiscale Modelling Tool. You can try the tool out for free online.
The DiODe team, together with Masters student Anna Font-Llenas, won the Best Paper Aware of ANTS 2018 for their paper ‘Quality-sensitive foraging by a robot swarm through virtual pheromone trails‘
We just published two papers in the Proceedings of the 11th International Conference on Swarm Intelligence (ANTS 2018) which will be held in Rome on October 29th-31st, 2018.
The paper Quality-sensitive foraging by a robot swarm through virtual pheromone trails by Anna Font Llenas, M. Salah Talamali, Xu Xu, James Marshall, and Andreagiovanni Reina showcases the functioning of ARK, our new super-cool infrastructure of Augmented Reality for Kilobots.
Check the video below!
The paper Simulating Kilobots within ARGoS: models and experimental validation by Carlo Pinciroli, M. Salah Talamali, Andreagiovanni Reina, James Marshall, and Vito Trianni proposes a new plugin for the ARGoS simulator that allows users to simulate Kilobots in a fast and realistic way, to use the same code in simulation and on robots, and to simulate the ARK infrastructure along with the Kilobots.
Giovanni co-ordinated a team of University of Sheffield and Sheffield Hallam University students who produced a new short film using our Kilobots. This was premiered at the Sheffield Robotics Showcase on June 26th, and is available to watch on the DiODe project You Tube channel…
James, Thomas, Giovanni, and Aldo will present four research outcomes from DiODe at the 11th European Conference on Mathematical and Theoretical Biology (ECMTB 2018) which will be held in Lisbon, Portugal, from 23 to 27 July, 2018.
James Marshall and Andreagiovanni Reina gave talks at the Conference on Collective Behaviour held at the International Centre for Theoretical Physics in Trieste.
Below, you can watch the talks from Giovanni and James. The list of all talks is available here.
Looking at honeybees in a colony as if they were neurons in a brain could help understand the basic mechanisms of human behaviour. A bee colony can be considered as a single superorganism, composed of tens of thousands of bees, which displays a coordinated response to external stimuli. Our recent paper, published in Scientific Reports and authored by Andreagiovanni Reina, Thomas Bose, Vito Trianni, and James Marshall, has shown that honeybee colonies might respond to stimuli in the same way other organisms, such as humans, do. The superorganism response is the result of interactions between individual bees; finding which type of interactions generate brain-like responses helps researchers to identify the general mechanisms generating these responses, and may ultimately lead to a better understanding of our brain.