New paper published in Computational Brain & Behavior

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.

New paper published in Neural Computation

Bose, T., Reina, A., Marshall, J. A. R. (2019) Inhibition and Excitation Shape Activity Selection: Effect of Oscillations in a Decision-Making CircuitNeural 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.

Two DiODe papers accepted

Two new papers with results of the DiODe project have been accepted recently. The review article entitled Collective Decision Making, which appeared in the journal Current Opinion in Behavioural Sciences, summarises recent progress in natural and artificial collective decision making. The other paper entitled A model of the best-of-N nest-site selection process in honeybees has been accepted for publication in Physical Review E and generalises in a theoretical study the nest site selection of honeybees to three and more options.

New PhD student joins DiODe Project

Salah Talamali joins the DiODe team beginning of May 2017 to investigate heterogeneities in collective decision making. His PhD project will involve the development of decision making algorithms and their implementation on the Kilobot platform, bringing the state of the art of artificial decision making closer to studying real-world scenarios using a swarm of robots.

Updated video on Youtube: Collective decision making of a swarm of robots

A swarm of 150 kilobot robots takes a value-sensitive decentralised decision between two options (red and blue). The swarm must select the best quality option if the quality is higher than a given threshold (in this study, greater than 1.5). In this experiment, the options have quality v=5 thus the swarm makes a decision for the option blue.
The overlaying coloured circles show the two options localised in the environment. The options are signalled through two static kilobot robots acting as beacons that send infrared messages with the option’s ID and quality. The robots light up their LED in a colour that corresponds to their internal commitment state: green for the uncommitted state and red and blue for commitment to the option of the respective colour.

Supplementary video of the paper:
A. Reina, T. Bose, V. Trianni and J. A. R. Marshall. “Effects of Spatiality on Value-Sensitive Decisions Made by Robot Swarms”. DARS 2016.