Using Synchronous Boolean Networks to Model Several Phenomena of Collective Behavior

In this paper, we propose an approach for modeling and analysis of a number of phenomena of collective behavior. By collectives we mean multi-agent systems that transition from one state to another at discrete moments of time. The behavior of a member of a collective (agent) is called conforming if...

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Main Authors:	Kochemazov, Stepan, Semenov, Alexander
Format:	Online
Language:	English
Published:	Public Library of Science 2014
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4272282/

id	pubmed-4272282
recordtype	oai_dc
spelling	pubmed-42722822014-12-26 Using Synchronous Boolean Networks to Model Several Phenomena of Collective Behavior Kochemazov, Stepan Semenov, Alexander Research Article In this paper, we propose an approach for modeling and analysis of a number of phenomena of collective behavior. By collectives we mean multi-agent systems that transition from one state to another at discrete moments of time. The behavior of a member of a collective (agent) is called conforming if the opinion of this agent at current time moment conforms to the opinion of some other agents at the previous time moment. We presume that at each moment of time every agent makes a decision by choosing from the set (where 1-decision corresponds to action and 0-decision corresponds to inaction). In our approach we model collective behavior with synchronous Boolean networks. We presume that in a network there can be agents that act at every moment of time. Such agents are called instigators. Also there can be agents that never act. Such agents are called loyalists. Agents that are neither instigators nor loyalists are called simple agents. We study two combinatorial problems. The first problem is to find a disposition of instigators that in several time moments transforms a network from a state where the majority of simple agents are inactive to a state with the majority of active agents. The second problem is to find a disposition of loyalists that returns the network to a state with the majority of inactive agents. Similar problems are studied for networks in which simple agents demonstrate the contrary to conforming behavior that we call anticonforming. We obtained several theoretical results regarding the behavior of collectives of agents with conforming or anticonforming behavior. In computational experiments we solved the described problems for randomly generated networks with several hundred vertices. We reduced corresponding combinatorial problems to the Boolean satisfiability problem (SAT) and used modern SAT solvers to solve the instances obtained. Public Library of Science 2014-12-19 /pmc/articles/PMC4272282/ /pubmed/25526612 http://dx.doi.org/10.1371/journal.pone.0115156 Text en © 2014 Kochemazov, Semenov http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Kochemazov, Stepan Semenov, Alexander
spellingShingle	Kochemazov, Stepan Semenov, Alexander Using Synchronous Boolean Networks to Model Several Phenomena of Collective Behavior
author_facet	Kochemazov, Stepan Semenov, Alexander
author_sort	Kochemazov, Stepan
title	Using Synchronous Boolean Networks to Model Several Phenomena of Collective Behavior
title_short	Using Synchronous Boolean Networks to Model Several Phenomena of Collective Behavior
title_full	Using Synchronous Boolean Networks to Model Several Phenomena of Collective Behavior
title_fullStr	Using Synchronous Boolean Networks to Model Several Phenomena of Collective Behavior
title_full_unstemmed	Using Synchronous Boolean Networks to Model Several Phenomena of Collective Behavior
title_sort	using synchronous boolean networks to model several phenomena of collective behavior
description	In this paper, we propose an approach for modeling and analysis of a number of phenomena of collective behavior. By collectives we mean multi-agent systems that transition from one state to another at discrete moments of time. The behavior of a member of a collective (agent) is called conforming if the opinion of this agent at current time moment conforms to the opinion of some other agents at the previous time moment. We presume that at each moment of time every agent makes a decision by choosing from the set (where 1-decision corresponds to action and 0-decision corresponds to inaction). In our approach we model collective behavior with synchronous Boolean networks. We presume that in a network there can be agents that act at every moment of time. Such agents are called instigators. Also there can be agents that never act. Such agents are called loyalists. Agents that are neither instigators nor loyalists are called simple agents. We study two combinatorial problems. The first problem is to find a disposition of instigators that in several time moments transforms a network from a state where the majority of simple agents are inactive to a state with the majority of active agents. The second problem is to find a disposition of loyalists that returns the network to a state with the majority of inactive agents. Similar problems are studied for networks in which simple agents demonstrate the contrary to conforming behavior that we call anticonforming. We obtained several theoretical results regarding the behavior of collectives of agents with conforming or anticonforming behavior. In computational experiments we solved the described problems for randomly generated networks with several hundred vertices. We reduced corresponding combinatorial problems to the Boolean satisfiability problem (SAT) and used modern SAT solvers to solve the instances obtained.
publisher	Public Library of Science
publishDate	2014
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4272282/
_version_	1613169277030891520

Using Synchronous Boolean Networks to Model Several Phenomena of Collective Behavior

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