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DiODe SIGNED

Distributed Algorithms for Optimal Decision-Making

Total Cost €

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EC-Contrib. €

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Partnership

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Project "DiODe" data sheet

The following table provides information about the project.

Coordinator
THE UNIVERSITY OF SHEFFIELD 

Organization address
address: FIRTH COURT WESTERN BANK
city: SHEFFIELD
postcode: S10 2TN
website: www.shef.ac.uk

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country United Kingdom [UK]
 Project website http://diode.group.shef.ac.uk/
 Total cost 1˙413˙705 €
 EC max contribution 1˙413˙705 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2014-CoG
 Funding Scheme ERC-COG
 Starting year 2015
 Duration (year-month-day) from 2015-08-01   to  2020-07-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    THE UNIVERSITY OF SHEFFIELD UK (SHEFFIELD) coordinator 1˙413˙705.00

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 Project objective

This grant will develop and translate a unifying framework for optimal decision-theory, and observations of natural systems, to design distributed algorithms for decentralised decision-making. This will enable a technological step-change in techniques for controlling distributed systems, primarily demonstrated during the grant by decentralised control of robot swarms. These algorithms and associated methodology will also provide hypotheses and tools to change the way scientists think about and interrogate natural decision mechanisms, from intracellular regulatory networks, via neural decision circuits, to decision-making populations of animals. Specific objectives are:

1. Distributed value-sensitive decision-making: undertake optimality analyses of the applicant’s existing decentralised decision-making algorithms based on observations of collective iterated voting-processes in honeybees, and extend these.

2. Distributed sampling and decision-making: design distributed mechanisms that implement optimal compromises between sampling information and making decisions based on that information.

3. Individual-confidence and distributed decision-making: translate machine learning theory to collective behaviour models, designing mechanisms in which weak decision-makers optimally combine their decisions to optimise group performance.

4. Optimal distributed decision-making in collective robotics: translate theory from objective 1 to 3 towards practical applications in artificial systems, demonstrated using collectively-deciding robots.

5. Development of tools for life scientists and validation of theoretical predictions in natural systems: interact with named collaborators to investigate identified decision mechanisms in single cells, in neural circuits, and in social groups. Develop accessible modelling tools to facilitate investigations by life scientists.

 Publications

year authors and title journal last update
List of publications.
2019 James Marshall
Comment on: Optimal policy for multi-alternative decisions.
published pages: , ISSN: , DOI: 10.1101/2019.12.18.880872
BiorXiv 2020-03-13
2019 Marshall, J. A. R., Kurvers, R., Krause, J., Wolf, M.
Quorums enable optimal pooling of independent judgements in biological systems.
published pages: , ISSN: 2050-084X, DOI: 10.7554/elife.40368.001
eLife 8:e40368 2020-03-13
2020 Thomas Bose, Angelo Pirrone, Andreagiovanni Reina, James A.R. Marshall
Comparison of magnitude-sensitive sequential sampling models in a simulation-based study
published pages: 102298, ISSN: 0022-2496, DOI: 10.1016/j.jmp.2019.102298
Journal of Mathematical Psychology 94 2020-03-13
2020 Thomas Bose, Freya Bottom, Andreagiovanni Reina, James A. R. Marshall
Frequency-Sensitivity and Magnitude-Sensitivity in Decision-Making: Predictions of a Theoretical Model-Based Study
published pages: 66-85, ISSN: 2522-0861, DOI: 10.1007/s42113-019-00031-4
Computational Brain & Behavior 3/1 2020-03-13
2020 Mohamed S. Talamali, Thomas Bose, Matthew Haire, Xu Xu, James A. R. Marshall, Andreagiovanni Reina
Sophisticated collective foraging with minimalist agents: a swarm robotics test
published pages: 25-56, ISSN: 1935-3812, DOI: 10.1007/s11721-019-00176-9
Swarm Intelligence 14/1 2020-03-13
2019 James A. R. Marshall, Andreagiovanni Reina, Thomas Bose
Multiscale Modelling Tool: Mathematical modelling of collective behaviour without the maths
published pages: e0222906, ISSN: 1932-6203, DOI: 10.1371/journal.pone.0222906
PLOS ONE 14/9 2020-03-13
2019 Andreagiovanni Reina, Viktor Ioannou, Junjin Chen, Lu Lu, Charles Kent, James A. R. Marshall
Robots as Actors in a Film: No War, A Robot Story.
published pages: , ISSN: , DOI:
arXiv 2020-03-13
2019 Thomas Bose, Andreagiovanni Reina, James A. R. Marshall
Inhibition and Excitation Shape Activity Selection: Effect of Oscillations in a Decision-Making Circuit
published pages: 870-896, ISSN: 0899-7667, DOI: 10.1162/neco_a_01185
Neural Computation 31/5 2020-03-13
2017 Thomas Bose, Andreagiovanni Reina, James AR Marshall
Collective decision-making
published pages: 30-34, ISSN: 2352-1546, DOI: 10.1016/j.cobeha.2017.03.004
Current Opinion in Behavioral Sciences 16 2019-06-06
2018 Andreagiovanni Reina, Thomas Bose, Vito Trianni, James A. R. Marshall
Psychophysical Laws and the Superorganism
published pages: , ISSN: 2045-2322, DOI: 10.1038/s41598-018-22616-y
Scientific Reports 8/1 2019-06-06
2017 Andreagiovanni Reina, James A. R. Marshall, Vito Trianni, Thomas Bose
Model of the best-of- N nest-site selection process in honeybees
published pages: , ISSN: 2470-0045, DOI: 10.1103/PhysRevE.95.052411
Physical Review E 95/5 2019-06-06
2017 Andreagiovanni Reina, Alex J. Cope, Eleftherios Nikolaidis, James A. R. Marshall, Chelsea Sabo
ARK: Augmented Reality for Kilobots
published pages: 1755-1761, ISSN: 2377-3766, DOI: 10.1109/LRA.2017.2700059
IEEE Robotics and Automation Letters 2/3 2019-06-06
2017 James A.R. Marshall, Gavin Brown, Andrew N. Radford
Individual Confidence-Weighting and Group Decision-Making
published pages: 636-645, ISSN: 0169-5347, DOI: 10.1016/j.tree.2017.06.004
Trends in Ecology & Evolution 32/9 2019-06-06
2018 Thomas O. Richardson, Charles Mullon, James A. R. Marshall, Nigel R. Franks, Thomas Schlegel
The influence of the few: a stable ‘oligarchy’ controls information flow in house-hunting ants
published pages: 20172726, ISSN: 0962-8452, DOI: 10.1098/rspb.2017.2726
Proceedings of the Royal Society B: Biological Sciences 285/1872 2019-06-06
2016 Reina A., Bose T., Trianni V., Marshall, J.A.R.
Effects of Spatiality on Value-Sensitive Decisions Made by Robot Swarms.
published pages: , ISSN: , DOI:
Proceedings of the 13th International Symposium on Distributed Autonomous Robotic Systems (DARS) 2019-06-06

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