Towards a Cognitive Design Pattern for Collective Decision-Making

We introduce the concept of cognitive design pattern to provide a design methodology for distributed multi-agent systems. A cognitive design pattern is a reusable solution to tackle problems requiring cognitive abilities (e.g., decision-making, attention, categorisation). It provides theoretical models and design guidelines to define the individual control rules in order to obtain a desired behaviour for the multiagent system as a whole. In this paper, we propose a cognitive design pattern for collective decision-making inspired by the nest-site selection behaviour of honeybee swarms. We illustrate how to apply the pattern to a case study involving spatial factors: the collective selection of the shortest path between two target areas. We analyse the dynamics of the multi-agent system and we show a very good agreement with the predictions of the macroscopic model.

[1]  Eliseo Ferrante,et al.  Majority-rule opinion dynamics with differential latency: a mechanism for self-organized collective decision-making , 2011, Swarm Intelligence.

[2]  N. Franks,et al.  A Mechanism for Value-Sensitive Decision-Making , 2013, PloS one.

[3]  Heiko Hamann Towards swarm calculus: urn models of collective decisions and universal properties of swarm performance , 2013, Swarm Intelligence.

[4]  Andrea Omicini,et al.  Design Patterns for Self-organising Systems , 2007, CEEMAS.

[5]  Thomas Schlegel,et al.  Stop Signals Provide Cross Inhibition in Collective Decision-making , 2022 .

[6]  Hong Zhang,et al.  Cooperative Decision-Making in Decentralized Multiple-Robot Systems: The Best-of-N Problem , 2009, IEEE/ASME Transactions on Mechatronics.

[7]  M. Dorigo,et al.  Self-Organized Discrimination of Resources , 2011, PloS one.

[8]  Wayne Nelson,et al.  Hazard Plotting for Incomplete Failure Data , 1969 .

[9]  Ralph Johnson,et al.  design patterns elements of reusable object oriented software , 2019 .

[10]  Roberto Montemanni,et al.  Design patterns from biology for distributed computing , 2006, TAAS.

[11]  I. Couzin Collective cognition in animal groups , 2009, Trends in Cognitive Sciences.

[12]  Tim Kovacs,et al.  On optimal decision-making in brains and social insect colonies , 2009, Journal of The Royal Society Interface.

[13]  Gabriela Lindemann,et al.  Multi-Agent Systems and Applications V, 5th International Central and Eastern European Conference on Multi-Agent Systems, CEEMAS 2007, Leipzig, Germany, September 25-27, 2007, Proceedings , 2007, CEEMAS.

[14]  Edward A. Codling,et al.  Random walk models in biology , 2008, Journal of The Royal Society Interface.

[15]  James A. R. Marshall,et al.  Swarm Cognition: an interdisciplinary approach to the study of self-organising biological collectives , 2011, Swarm Intelligence.