Under objective 1, we published further papers on optimal decentralised algorithms in leading venues including eLife, Neural Computation, Computational Brain & Behavior, and Journal of Mathematical Psychology; this work covers a variety of topics, from optimal quorum usage, to neural action selection models, to model mimicry in data fitting. The PI also published a preprint commentary on optimal value-based decisions (bioRxiv) which will be supplemented with novel experimental data for publication during the next reporting period. In the 36 month report we described how our work on generalising speed-value trade-offs to choices over more than two alternatives, including symmetry breaking and best-of-N decision-making, (described in the 18 month report) was accepted for publication in Physical Review E. It was an Editor’s Suggestion in that journal, and a research highlight in Nature Physics. We have also published a paper on replicating psychophysical, value-sensitive behaviour using the same collective decision-making model, in Scientific Reports, as described in the 30 month report.
Under objective 2, work on combining sampling and decision-making in a unified formulation has continued, based on an approach pioneered by the PI in psychophysics (Cassey et al., 2013, PLoS one). Additionally, through an Erasmus traineeship to Pascal van Beek (Eindhoven) work has been conducted on analysing the optimal ongoing decision-making strategy for minimising expected cost from a decision, where cost is defined in a very general Euclidean way over a state-space following earlier work by the PI (Marshall et al., 2015, Current Zoology).
Under objective 3, the review article on confidence and collective decision-making, mentioned in the 18 month report, was published in Trends in Ecology and Evolution, where it featured on the journal cover, as described in the 30 month report. While the ERC Proof of Concept grant on this was unsuccessful, the work has been further developed for publication with an external collaborator.
Under objective 4, work on instantiating our theory on the Kilobot platform has progressed, with publications in prestigious venues such as ICRA, and in Swarm Intelligence; Prior value-sensitive decision-making work in Kilobot swarms was presented at Distributed and Autonomous Robotics Systems 2016 (see Publications), as described in the 30 month report. This work has built on our sophisticated Augmented Reality for Kilobots system (see §1.2) described in the 18 month report, which was accepted for publication in Robotics and Automation Letters and presented at IROS 2017, and its subsequent integration with the ARGoS robotics simulator, which was accepted for publication and presentation at the Eleventh International Conference on Swarm Intelligence (Pinciroli et al., ANTS 2018), alongside an MSc student project hosted by the project team, on value-sensitive pheromone-based collective foraging in robot swarms (Font Llenas et al., ANTS 2018; awarded as the best paper of the conference).
Under objective 5, our work on our novel tool for modelling of collective behaviour systems by life scientists and engineers (see §1.2§) was released as open source (mumot.readthedocs.io) and published in PLoS one; as described in the 30 month report, this is now stored on a public GitHub repository providing a publicly-accessible executable implementation via MyBinder. In addition, project PhD student Aldo Segura has continued modelling unicellular decision-making, and has interacted with named external experimental collaborator Prof Peter Swain (see ‘Progress beyond the state of the art’). Work on theoretical neuroscience, and in collaboration with external project partners Max Wolf and colleagues, was published as described in the report on objective 1.
