Majority Rule with Differential Latency: An Absorbing Markov Chain to Model Consensus
We study collective decision-making in a swarm of robots. We consider the majority rule with differential latency: robots randomly form teams, make a decision following the majority rule, and then turn in a latent state whose duration depends on the decision made. While latent, robots do not participate in the decision mechanism, thus, the differential latency provides a positive feedback that favors the decision with the shortest latency. We analyze the dynamics using a discrete, time-homogeneous, absorbing Markov chain.
The research leading to the results presented in this paper has received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007–2013)/ERC grant agreement no. 246939. Mauro Birattari and Marco Dorigo acknowledge support from the F.R.S.-FNRS of Belgium’s Wallonia-Brussels Federation.
- 1.Banisch S, Lima R, Araujo T (2011) Agent based models and opinion dynamics as Markov chains. arXiv:1108.1716v2
- 6.Massink M, Brambilla M, Latella D, Dorigo M, Birattari M (2012, in press) Analysing robot decision-making with bio-pepa. In: Proceedings of the eighth international conference on swarm intelligence, ANTS 2012. Lecture notes in computer science. Springer, Berlin Google Scholar