Coupled stochastic differential equations and collective decision making in the two-alternative forced-choice task

Ioannis Poulakakis, Luca Scardovi, Naomi Ehrich Leonard

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Scopus citations

Abstract

This paper investigates the effect of coupling in a collective decision-making scenario, in which the task is to correctly identify a (noisy) stimulus between two known alternatives. Multiple interconnected decision-making units, each represented by a Drift-Diffusion Model (DDM), accumulate evidence toward a decision. A number of different graph topologies among the DDM's are considered, and their effect on the accuracy of the decision is investigated. It is deduced that, for the same stimuli, the average of the collected evidence increases linearly with time toward the correct decision regardless of the communication topology. However, the uncertainty associated with the process is affected by the interconnection graph, implying that certain topologies are better than others.

Original languageEnglish (US)
Title of host publicationProceedings of the 2010 American Control Conference, ACC 2010
PublisherIEEE Computer Society
Pages69-74
Number of pages6
ISBN (Print)9781424474264
DOIs
StatePublished - Jan 1 2010

Publication series

NameProceedings of the 2010 American Control Conference, ACC 2010

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering

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    Poulakakis, I., Scardovi, L., & Leonard, N. E. (2010). Coupled stochastic differential equations and collective decision making in the two-alternative forced-choice task. In Proceedings of the 2010 American Control Conference, ACC 2010 (pp. 69-74). [5530660] (Proceedings of the 2010 American Control Conference, ACC 2010). IEEE Computer Society. https://doi.org/10.1109/acc.2010.5530660