
Previous Article
A case study of optimal inputoutput system with sampleddata control: Ding et al. force and fatigue muscular control model
 NHM Home
 This Issue

Next Article
Optimal stopping for responseguided dosing
A network model of immigration: Enclave formation vs. cultural integration
1.  Dept. of Biomathematics, UCLA, Los Angeles, CA 900951766, USA 
2.  Dept. of Mathematics, CSUN, Los Angeles, CA 913308313, USA 
3.  Dept. of Mathematics, UCLA, Los Angeles, CA 900951555, USA 
Successfully integrating newcomers into native communities has become a key issue for policy makers, as the growing number of migrants has brought cultural diversity, new skills, but also, societal tensions to receiving countries. We develop an agentbased network model to study interacting "hosts" and "guests" and to identify the conditions under which cooperative/integrated or uncooperative/segregated societies arise. Players are assumed to seek socioeconomic prosperity through game theoretic rules that shift network links, and cultural acceptance through opinion dynamics. We find that the main predictor of integration under given initial conditions is the timescale associated with cultural adjustment relative to social link remodeling, for both guests and hosts. Fast cultural adjustment results in cooperation and the establishment of hostguest connections that are sustained over long times. Conversely, fast social link remodeling leads to the irreversible formation of isolated enclaves, as migrants and natives optimize their socioeconomic gains through ingroup connections. We discuss how migrant population sizes and increasing socioeconomic rewards for hostguest interactions, through governmental incentives or by admitting migrants with highly desirable skills, may affect the overall immigrant experience.
References:
[1] 
R. Axelrod, The dissemination of culture: A model with local convergence and global polarization, The Journal of Conflict Resolution, 41 (1997), 203226. doi: 10.1177/0022002797041002001. Google Scholar 
[2] 
P. Barron, K. Kaiser and M. Pradhan, Local Conflict in Indonesia: Measuring Incidence and Identifying Patterns, World Bank Policy Research Paper 3384, 2004. Google Scholar 
[3] 
J. W. Berry, Acculturation and adaptation in a new society, International Migration Quarterly Review, 30 (1992), 6985. doi: 10.1111/j.14682435.1992.tb00776.x. Google Scholar 
[4] 
J. W. Berry, Living successfully in two cultures, International Journal of Intercultural Relations, 29 (2005), 697712. Google Scholar 
[5] 
J. W. Berry, U. Kim, T. Minde and D. Mok, Comparative studies of acculturative stress, The International Migration Review, 21 (1987), 491511. Google Scholar 
[6] 
P. Boyle, K. Halfacree and V. Robinson, Exploring contemporary migration, 2nd edition, Pearson Education Limited, London and New York, 2013. Google Scholar 
[7]  S. Castles and M. J. Miller, The Age of Migration: International Population Movements in the Modern World, The Guilford Press, New York, 2003. Google Scholar 
[8] 
E. M. Chaney, Foreword: The world economy and contemporary migration, The International Migration Review, 13 (1979), 204212. doi: 10.2307/2545027. Google Scholar 
[9] 
Y.S. Chiang, Cooperation could evolve in complex networks when activated conditionally on network characteristics, Journal of Artificial Societies and Social Simulation, 16 (2013), 6. doi: 10.18564/jasss.2148. Google Scholar 
[10] 
Y.L. Chuang, M. R. D'Orsogna and T. Chou, A bistable belief dynamics model for radicalization within sectarian conflict, Quarterly of Applied Mathematics, 75 (2017), 1937. doi: 10.1090/qam/1446. Google Scholar 
[11] 
M. D. Cohen, R. L. Riolo and R. Axelrod, The role of social structure in the maintenance of cooperative regimes, Rationality and Society, 13 (2001), 532. doi: 10.1177/104346301013001001. Google Scholar 
[12] 
M. H. Crawford and B. C. Campbell (eds.), Causes and Consequences of Human Migration, Cambridge University Press, Cambridge, UK, 2012. doi: 10.1017/CBO9781139003308. Google Scholar 
[13] 
A. P. Damm, Determinants of recent immigrants'location choices: Quasiexperimental evidence, Journal of Population Economics, 22 (2009), 145174. Google Scholar 
[14] 
G. Deffuant, D. Neau, F. Amblard and G. Weisbuch, Mixing beliefs among interacting agents, Advances in Complex Systems, 3 (2000), 8798. doi: 10.1142/S0219525900000078. Google Scholar 
[15] 
M. H. DeGroot, Reaching a consensus, Journal of the American Statistical Association, 69 (1974), 118121. Google Scholar 
[16] 
K. Fehl, D. J. van der Post and D. Semmann, Coevolution of behaviour and social network structure promotes human cooperation, Ecology Letters, 14 (2011), 546551. doi: 10.1111/j.14610248.2011.01615.x. Google Scholar 
[17] 
K. Felijakowski and R. Kosinski, Bounded confidence model in complex networks, International Journal of Modern Physics C, 24 (2013), 1350049, 12pp. doi: 10.1142/S0129183113500496. Google Scholar 
[18] 
K. Felijakowski and R. Kosinski, Opinion formation and selforganization in a social network in an intelligent agent system, ACTA Physica Polonica B, 45 (2014), 21232134. doi: 10.5506/APhysPolB.45.2123. Google Scholar 
[19] 
M. Fossett, Ethnic preferences, social distance dynamics, and residential segregation: Theoretical explorations using simulation analysis, The Journal of Mathematical Sociology, 30 (2006), 185273. doi: 10.1080/00222500500544052. Google Scholar 
[20] 
N. E. Friedkin, Choice shift and group polarization, American Sociological Review, 64 (1999), 856875. Google Scholar 
[21] 
A. Gabel, P. L. Krapivsky and S. Redner, Highly dispersed networks by enhanced redirection, Physical Review E, 88 (2013), 050802(R). doi: 10.1103/PhysRevE.88.050802. Google Scholar 
[22] 
S. Galam, Heterogeneous beliefs, segregation, and extremism in the making of public opinions, Physical Review E, 71 (2005), 046123. doi: 10.1103/PhysRevE.71.046123. Google Scholar 
[23] 
S. Galam, Stubbornness as an unfortunate key to win a public debate: An illustration from sociophysics, Society, 15 (2016), 117130. doi: 10.1007/s112990150175y. Google Scholar 
[24] 
S. Galam and M. A. Javarone, Modeling radicalization phenomena in heterogeneous populations, PLOS One, 11 (2016), e0155407. doi: 10.1371/journal.pone.0155407. Google Scholar 
[25] 
B. Golub and M. O. Jackson, Naíve learning in social networks and the wisdom of crowds, American Economic Journal: Microeconomics, 2 (2010), 112149. doi: 10.1257/mic.2.1.112. Google Scholar 
[26] 
D. Hales, Cooperation without memory or space: Tags, groups and the Prisoner's Dilemma, in MultiAgentBased Simulation. (eds. S. Moss and P. Davidsson), Springer, Berlin/Heidelberg, 2000, 157–166. doi: 10.1007/3540445617_12. Google Scholar 
[27] 
R. A. Hammond and R. Axelrod, The evolution of ethnocentrism, Journal of Conflict Resolution, 50 (2006), 926936. doi: 10.1177/0022002706293470. Google Scholar 
[28] 
D. J. Haw and J. Hogan, A dynamical systems model of unorganized segregation, The Journal of Mathematical Sociology, 42 (2018), 113127. doi: 10.1080/0022250X.2018.1427091. Google Scholar 
[29] 
A. D. Henry, P. Pralat and C.Q. Zhang, Emergence of segregation in evolving social networks, PNAS, 108 (2011), 86058610. doi: 10.1073/pnas.1014486108. Google Scholar 
[30]  P. Ireland, Becoming Europe: Immigration Integration And The Welfare State, University of Pittsburgh Press, Pittsburgh, PA, 2004. Google Scholar 
[31] 
M. A. Javarone, A. E. Atzeni and S. Galam, Emergence of cooperation in the Prisoner's Dilemma driven by conformity, in Applications of Evolutionary Computation. EvoApplications 2015. Lecture Notes in Computer Science (eds. A. Mora and G. Squillero), vol. 9028, Springer, Cham, 2015, 155–163. doi: 10.1007/9783319165493_13. Google Scholar 
[32] 
W. Kandel and J. Cromartie, New patterns of Hispanic settlement in rural America, Technical Report 99, United States Department of Agriculture, 2004. Google Scholar 
[33] 
T. B. Klos, Decentralized interaction and coadaptation in the repeated prisoners dilemma, Computational and Mathematical Organization Theory, 5 (1999), 147165. Google Scholar 
[34] 
R. Koopmans, Tradeoffs between equality and difference: Immigrant integration, multiculturalism and the welfare state in crossnational perspective, Journal of Ethnic and Migration Studies, 36 (2010), 126. doi: 10.1080/13691830903250881. Google Scholar 
[35] 
U. Krause, A discrete nonlinear and nonautonomous model of consensus formation, in Communications in Difference Equations (eds. S. Elaydi, G. Ladas, J. Popenda and J. Rakowski), Amsterdam: Gordon and Breach, 2000, 227–236. Google Scholar 
[36] 
D. T. Lichter, D. Parisi and M. C. Taquino, Emerging patterns of Hispanic residential segregation: Lessons from rural and small–town America, Rural Sociology, 81 (2016), 483518. doi: 10.1111/ruso.12108. Google Scholar 
[37] 
D. T. Lichter, D. Parisi, M. C. Taquino and S. M. Grice, Residential segregation in new Hispanic destinations: Cities, suburbs, and rural communities compared, Social Science Research, 39 (2010), 215230. doi: 10.1016/j.ssresearch.2009.08.006. Google Scholar 
[38] 
A. Németh and K. Takács, The evolution of altruism in spatially structured populations, Journal of Artificial Societies and Social Simulations, 10 (2007), 113. Google Scholar 
[39] 
A. Nowak, J. Szamrej and B. Latané, From private attitude to public opinion: A dynamic theory of social impact, Psychological Review, 97 (1990), 362376. doi: 10.1037/0033295X.97.3.362. Google Scholar 
[40] 
N. Priest, Y. Paradies, A. Ferdinand, L. Rouhani and M. Kelaher, Patterns of intergroup contact in public spaces: Microecology of segregation in Australian communities, Societies, 4 (2014), 3044. doi: 10.3390/soc4010030. Google Scholar 
[41] 
R. Riolo, The Effects of TagMediated Selection of Partners in Evolving Populations Playing the Iterated Prisoner's Dilemma, Technical report, Santa Fe Institute, Santa Fe, NM, 1997. Google Scholar 
[42] 
R. L. Riolo, M. D. Cohen and R. Axelrod, Evolution of cooperation without reciprocity, Nature, 414 (2001), 441443. doi: 10.1038/35106555. Google Scholar 
[43] 
F. C. Santos, J. M. Pacheco and T. Lenaerts, Cooperation prevails when individuals adjust their social ties, PLoS Computational Biology, 2 (2006), e140. doi: 10.1371/journal.pcbi.0020140. Google Scholar 
[44] 
M. Semyonov and A. Tyree, Community segregation and the costs of ethnic subordination, Social Forces, 59 (1981), 649666. Google Scholar 
[45] 
E. S. Stewart, UK dispersal policy and onward migration: Mapping the current state of knowledge, Journal of Refugee Studies, 25 (2012), 2549. doi: 10.1093/jrs/fer039. Google Scholar 
[46] 
A. Szolnoki and M. Perc, Competition of tolerant strategies in the spatial public goods game, New Journal of Physics, 18 (2016), 083021. doi: 10.1088/13672630/18/8/083021. Google Scholar 
[47] 
UNHCR, Global trends: Forced displacement in 2017, Technical report, The UN Refugee Agency, The United Nations, 2018, http://www.unhcr.org/5b27be547.pdf. Google Scholar 
[48] 
Q. Wang, H. Wang, Z. Zhang, Y. Li, Y. Liu and M. Perc, Heterogeneous investments promote cooperation in evolutionary public goods games, Physica A, 502 (2018), 570575. Google Scholar 
[49] 
D. J. Watts and S. H. Strogatz, Collective dynamics of 'smallworld' networks, Nature, 393 (1998), 440442. Google Scholar 
[50] 
G. Weisbuch, G. Deffuant, F. Amblard and J.P. Nadal, Meet, discuss, and segregate, Complexity, 7 (2002), 5563. doi: 10.1002/cplx.10031. Google Scholar 
[51] 
J. S. White, R. Hamad, X. Li, S. Basu, H. Ohlsson, J. Sundquist and K. Sundquist, Longterm effects of neighbourhood deprivation on diabetes risk: Quasiexperimental evidence from a refugee dispersal policy in Sweden, The Lancet Diabetes and Endocrinology, 4 (2016), 517524. doi: 10.1016/S22138587(16)300092. Google Scholar 
show all references
References:
[1] 
R. Axelrod, The dissemination of culture: A model with local convergence and global polarization, The Journal of Conflict Resolution, 41 (1997), 203226. doi: 10.1177/0022002797041002001. Google Scholar 
[2] 
P. Barron, K. Kaiser and M. Pradhan, Local Conflict in Indonesia: Measuring Incidence and Identifying Patterns, World Bank Policy Research Paper 3384, 2004. Google Scholar 
[3] 
J. W. Berry, Acculturation and adaptation in a new society, International Migration Quarterly Review, 30 (1992), 6985. doi: 10.1111/j.14682435.1992.tb00776.x. Google Scholar 
[4] 
J. W. Berry, Living successfully in two cultures, International Journal of Intercultural Relations, 29 (2005), 697712. Google Scholar 
[5] 
J. W. Berry, U. Kim, T. Minde and D. Mok, Comparative studies of acculturative stress, The International Migration Review, 21 (1987), 491511. Google Scholar 
[6] 
P. Boyle, K. Halfacree and V. Robinson, Exploring contemporary migration, 2nd edition, Pearson Education Limited, London and New York, 2013. Google Scholar 
[7]  S. Castles and M. J. Miller, The Age of Migration: International Population Movements in the Modern World, The Guilford Press, New York, 2003. Google Scholar 
[8] 
E. M. Chaney, Foreword: The world economy and contemporary migration, The International Migration Review, 13 (1979), 204212. doi: 10.2307/2545027. Google Scholar 
[9] 
Y.S. Chiang, Cooperation could evolve in complex networks when activated conditionally on network characteristics, Journal of Artificial Societies and Social Simulation, 16 (2013), 6. doi: 10.18564/jasss.2148. Google Scholar 
[10] 
Y.L. Chuang, M. R. D'Orsogna and T. Chou, A bistable belief dynamics model for radicalization within sectarian conflict, Quarterly of Applied Mathematics, 75 (2017), 1937. doi: 10.1090/qam/1446. Google Scholar 
[11] 
M. D. Cohen, R. L. Riolo and R. Axelrod, The role of social structure in the maintenance of cooperative regimes, Rationality and Society, 13 (2001), 532. doi: 10.1177/104346301013001001. Google Scholar 
[12] 
M. H. Crawford and B. C. Campbell (eds.), Causes and Consequences of Human Migration, Cambridge University Press, Cambridge, UK, 2012. doi: 10.1017/CBO9781139003308. Google Scholar 
[13] 
A. P. Damm, Determinants of recent immigrants'location choices: Quasiexperimental evidence, Journal of Population Economics, 22 (2009), 145174. Google Scholar 
[14] 
G. Deffuant, D. Neau, F. Amblard and G. Weisbuch, Mixing beliefs among interacting agents, Advances in Complex Systems, 3 (2000), 8798. doi: 10.1142/S0219525900000078. Google Scholar 
[15] 
M. H. DeGroot, Reaching a consensus, Journal of the American Statistical Association, 69 (1974), 118121. Google Scholar 
[16] 
K. Fehl, D. J. van der Post and D. Semmann, Coevolution of behaviour and social network structure promotes human cooperation, Ecology Letters, 14 (2011), 546551. doi: 10.1111/j.14610248.2011.01615.x. Google Scholar 
[17] 
K. Felijakowski and R. Kosinski, Bounded confidence model in complex networks, International Journal of Modern Physics C, 24 (2013), 1350049, 12pp. doi: 10.1142/S0129183113500496. Google Scholar 
[18] 
K. Felijakowski and R. Kosinski, Opinion formation and selforganization in a social network in an intelligent agent system, ACTA Physica Polonica B, 45 (2014), 21232134. doi: 10.5506/APhysPolB.45.2123. Google Scholar 
[19] 
M. Fossett, Ethnic preferences, social distance dynamics, and residential segregation: Theoretical explorations using simulation analysis, The Journal of Mathematical Sociology, 30 (2006), 185273. doi: 10.1080/00222500500544052. Google Scholar 
[20] 
N. E. Friedkin, Choice shift and group polarization, American Sociological Review, 64 (1999), 856875. Google Scholar 
[21] 
A. Gabel, P. L. Krapivsky and S. Redner, Highly dispersed networks by enhanced redirection, Physical Review E, 88 (2013), 050802(R). doi: 10.1103/PhysRevE.88.050802. Google Scholar 
[22] 
S. Galam, Heterogeneous beliefs, segregation, and extremism in the making of public opinions, Physical Review E, 71 (2005), 046123. doi: 10.1103/PhysRevE.71.046123. Google Scholar 
[23] 
S. Galam, Stubbornness as an unfortunate key to win a public debate: An illustration from sociophysics, Society, 15 (2016), 117130. doi: 10.1007/s112990150175y. Google Scholar 
[24] 
S. Galam and M. A. Javarone, Modeling radicalization phenomena in heterogeneous populations, PLOS One, 11 (2016), e0155407. doi: 10.1371/journal.pone.0155407. Google Scholar 
[25] 
B. Golub and M. O. Jackson, Naíve learning in social networks and the wisdom of crowds, American Economic Journal: Microeconomics, 2 (2010), 112149. doi: 10.1257/mic.2.1.112. Google Scholar 
[26] 
D. Hales, Cooperation without memory or space: Tags, groups and the Prisoner's Dilemma, in MultiAgentBased Simulation. (eds. S. Moss and P. Davidsson), Springer, Berlin/Heidelberg, 2000, 157–166. doi: 10.1007/3540445617_12. Google Scholar 
[27] 
R. A. Hammond and R. Axelrod, The evolution of ethnocentrism, Journal of Conflict Resolution, 50 (2006), 926936. doi: 10.1177/0022002706293470. Google Scholar 
[28] 
D. J. Haw and J. Hogan, A dynamical systems model of unorganized segregation, The Journal of Mathematical Sociology, 42 (2018), 113127. doi: 10.1080/0022250X.2018.1427091. Google Scholar 
[29] 
A. D. Henry, P. Pralat and C.Q. Zhang, Emergence of segregation in evolving social networks, PNAS, 108 (2011), 86058610. doi: 10.1073/pnas.1014486108. Google Scholar 
[30]  P. Ireland, Becoming Europe: Immigration Integration And The Welfare State, University of Pittsburgh Press, Pittsburgh, PA, 2004. Google Scholar 
[31] 
M. A. Javarone, A. E. Atzeni and S. Galam, Emergence of cooperation in the Prisoner's Dilemma driven by conformity, in Applications of Evolutionary Computation. EvoApplications 2015. Lecture Notes in Computer Science (eds. A. Mora and G. Squillero), vol. 9028, Springer, Cham, 2015, 155–163. doi: 10.1007/9783319165493_13. Google Scholar 
[32] 
W. Kandel and J. Cromartie, New patterns of Hispanic settlement in rural America, Technical Report 99, United States Department of Agriculture, 2004. Google Scholar 
[33] 
T. B. Klos, Decentralized interaction and coadaptation in the repeated prisoners dilemma, Computational and Mathematical Organization Theory, 5 (1999), 147165. Google Scholar 
[34] 
R. Koopmans, Tradeoffs between equality and difference: Immigrant integration, multiculturalism and the welfare state in crossnational perspective, Journal of Ethnic and Migration Studies, 36 (2010), 126. doi: 10.1080/13691830903250881. Google Scholar 
[35] 
U. Krause, A discrete nonlinear and nonautonomous model of consensus formation, in Communications in Difference Equations (eds. S. Elaydi, G. Ladas, J. Popenda and J. Rakowski), Amsterdam: Gordon and Breach, 2000, 227–236. Google Scholar 
[36] 
D. T. Lichter, D. Parisi and M. C. Taquino, Emerging patterns of Hispanic residential segregation: Lessons from rural and small–town America, Rural Sociology, 81 (2016), 483518. doi: 10.1111/ruso.12108. Google Scholar 
[37] 
D. T. Lichter, D. Parisi, M. C. Taquino and S. M. Grice, Residential segregation in new Hispanic destinations: Cities, suburbs, and rural communities compared, Social Science Research, 39 (2010), 215230. doi: 10.1016/j.ssresearch.2009.08.006. Google Scholar 
[38] 
A. Németh and K. Takács, The evolution of altruism in spatially structured populations, Journal of Artificial Societies and Social Simulations, 10 (2007), 113. Google Scholar 
[39] 
A. Nowak, J. Szamrej and B. Latané, From private attitude to public opinion: A dynamic theory of social impact, Psychological Review, 97 (1990), 362376. doi: 10.1037/0033295X.97.3.362. Google Scholar 
[40] 
N. Priest, Y. Paradies, A. Ferdinand, L. Rouhani and M. Kelaher, Patterns of intergroup contact in public spaces: Microecology of segregation in Australian communities, Societies, 4 (2014), 3044. doi: 10.3390/soc4010030. Google Scholar 
[41] 
R. Riolo, The Effects of TagMediated Selection of Partners in Evolving Populations Playing the Iterated Prisoner's Dilemma, Technical report, Santa Fe Institute, Santa Fe, NM, 1997. Google Scholar 
[42] 
R. L. Riolo, M. D. Cohen and R. Axelrod, Evolution of cooperation without reciprocity, Nature, 414 (2001), 441443. doi: 10.1038/35106555. Google Scholar 
[43] 
F. C. Santos, J. M. Pacheco and T. Lenaerts, Cooperation prevails when individuals adjust their social ties, PLoS Computational Biology, 2 (2006), e140. doi: 10.1371/journal.pcbi.0020140. Google Scholar 
[44] 
M. Semyonov and A. Tyree, Community segregation and the costs of ethnic subordination, Social Forces, 59 (1981), 649666. Google Scholar 
[45] 
E. S. Stewart, UK dispersal policy and onward migration: Mapping the current state of knowledge, Journal of Refugee Studies, 25 (2012), 2549. doi: 10.1093/jrs/fer039. Google Scholar 
[46] 
A. Szolnoki and M. Perc, Competition of tolerant strategies in the spatial public goods game, New Journal of Physics, 18 (2016), 083021. doi: 10.1088/13672630/18/8/083021. Google Scholar 
[47] 
UNHCR, Global trends: Forced displacement in 2017, Technical report, The UN Refugee Agency, The United Nations, 2018, http://www.unhcr.org/5b27be547.pdf. Google Scholar 
[48] 
Q. Wang, H. Wang, Z. Zhang, Y. Li, Y. Liu and M. Perc, Heterogeneous investments promote cooperation in evolutionary public goods games, Physica A, 502 (2018), 570575. Google Scholar 
[49] 
D. J. Watts and S. H. Strogatz, Collective dynamics of 'smallworld' networks, Nature, 393 (1998), 440442. Google Scholar 
[50] 
G. Weisbuch, G. Deffuant, F. Amblard and J.P. Nadal, Meet, discuss, and segregate, Complexity, 7 (2002), 5563. doi: 10.1002/cplx.10031. Google Scholar 
[51] 
J. S. White, R. Hamad, X. Li, S. Basu, H. Ohlsson, J. Sundquist and K. Sundquist, Longterm effects of neighbourhood deprivation on diabetes risk: Quasiexperimental evidence from a refugee dispersal policy in Sweden, The Lancet Diabetes and Endocrinology, 4 (2016), 517524. doi: 10.1016/S22138587(16)300092. Google Scholar 
Symbol  Description  default values 
 attitude  1 to 1 
 maximal utility through ingroup connection  
 maximal utility through outgroup connection  
 sensitivity to attitude difference  
 attitude adjustment timescale  
 cost of adding connections  
 total population  
 guest population  
 host population  
Symbol  Description  default values 
 attitude  1 to 1 
 maximal utility through ingroup connection  
 maximal utility through outgroup connection  
 sensitivity to attitude difference  
 attitude adjustment timescale  
 cost of adding connections  
 total population  
 guest population  
 host population  
[1] 
Holly Gaff. Preliminary analysis of an agentbased model for a tickborne disease. Mathematical Biosciences & Engineering, 2011, 8 (2) : 463473. doi: 10.3934/mbe.2011.8.463 
[2] 
Gianluca D'Antonio, Paul Macklin, Luigi Preziosi. An agentbased model for elastoplastic mechanical interactions between cells, basement membrane and extracellular matrix. Mathematical Biosciences & Engineering, 2013, 10 (1) : 75101. doi: 10.3934/mbe.2013.10.75 
[3] 
Marina Dolfin, Mirosław Lachowicz. Modeling opinion dynamics: How the network enhances consensus. Networks & Heterogeneous Media, 2015, 10 (4) : 877896. doi: 10.3934/nhm.2015.10.877 
[4] 
SeungYeal Ha, Dohyun Kim, Jaeseung Lee, Se Eun Noh. Emergent dynamics of an orientation flocking model for multiagent system. Discrete & Continuous Dynamical Systems, 2020, 40 (4) : 20372060. doi: 10.3934/dcds.2020105 
[5] 
Rainer Hegselmann, Ulrich Krause. Opinion dynamics under the influence of radical groups, charismatic leaders, and other constant signals: A simple unifying model. Networks & Heterogeneous Media, 2015, 10 (3) : 477509. doi: 10.3934/nhm.2015.10.477 
[6] 
Dieter Armbruster, Christian Ringhofer, Andrea Thatcher. A kinetic model for an agent based market simulation. Networks & Heterogeneous Media, 2015, 10 (3) : 527542. doi: 10.3934/nhm.2015.10.527 
[7] 
Linhe Zhu, Wenshan Liu. Spatial dynamics and optimization method for a network propagation model in a shifting environment. Discrete & Continuous Dynamical Systems, 2021, 41 (4) : 18431874. doi: 10.3934/dcds.2020342 
[8] 
Astridh Boccabella, Roberto Natalini, Lorenzo Pareschi. On a continuous mixed strategies model for evolutionary game theory. Kinetic & Related Models, 2011, 4 (1) : 187213. doi: 10.3934/krm.2011.4.187 
[9] 
Anna Lisa Amadori, Astridh Boccabella, Roberto Natalini. A hyperbolic model of spatial evolutionary game theory. Communications on Pure & Applied Analysis, 2012, 11 (3) : 9811002. doi: 10.3934/cpaa.2012.11.981 
[10] 
Daewa Kim, Annalisa Quaini. A kinetic theory approach to model pedestrian dynamics in bounded domains with obstacles. Kinetic & Related Models, 2019, 12 (6) : 12731296. doi: 10.3934/krm.2019049 
[11] 
Paula Federico, Dobromir T. Dimitrov, Gary F. McCracken. Bat population dynamics: multilevel model based on individuals' energetics. Mathematical Biosciences & Engineering, 2008, 5 (4) : 743756. doi: 10.3934/mbe.2008.5.743 
[12] 
Marco Caponigro, Anna Chiara Lai, Benedetto Piccoli. A nonlinear model of opinion formation on the sphere. Discrete & Continuous Dynamical Systems, 2015, 35 (9) : 42414268. doi: 10.3934/dcds.2015.35.4241 
[13] 
Aylin Aydoğdu, Sean T. McQuade, Nastassia Pouradier Duteil. Opinion Dynamics on a General Compact Riemannian Manifold. Networks & Heterogeneous Media, 2017, 12 (3) : 489523. doi: 10.3934/nhm.2017021 
[14] 
Robin Cohen, Alan Tsang, Krishna Vaidyanathan, Haotian Zhang. Analyzing opinion dynamics in online social networks. Big Data & Information Analytics, 2016, 1 (4) : 279298. doi: 10.3934/bdia.2016011 
[15] 
Yannick Viossat. Game dynamics and Nash equilibria. Journal of Dynamics & Games, 2014, 1 (3) : 537553. doi: 10.3934/jdg.2014.1.537 
[16] 
AminaAicha Khennaoui, A. Othman Almatroud, Adel Ouannas, M. Mossa Alsawalha, Giuseppe Grassi, VietThanh Pham. The effect of caputo fractional difference operator on a novel game theory model. Discrete & Continuous Dynamical Systems  B, 2021, 26 (8) : 45494565. doi: 10.3934/dcdsb.2020302 
[17] 
Jan Prüss, Laurent PujoMenjouet, G.F. Webb, Rico Zacher. Analysis of a model for the dynamics of prions. Discrete & Continuous Dynamical Systems  B, 2006, 6 (1) : 225235. doi: 10.3934/dcdsb.2006.6.225 
[18] 
Laurent Boudin, Francesco Salvarani. The quasiinvariant limit for a kinetic model of sociological collective behavior. Kinetic & Related Models, 2009, 2 (3) : 433449. doi: 10.3934/krm.2009.2.433 
[19] 
Bruno Buonomo, Giuseppe Carbone, Alberto d'Onofrio. Effect of seasonality on the dynamics of an imitationbased vaccination model with public health intervention. Mathematical Biosciences & Engineering, 2018, 15 (1) : 299321. doi: 10.3934/mbe.2018013 
[20] 
Zhijian Yang, Ke Li. Longtime dynamics for an elastic waveguide model. Conference Publications, 2013, 2013 (special) : 797806. doi: 10.3934/proc.2013.2013.797 
2020 Impact Factor: 1.213
Tools
Metrics
Other articles
by authors
[Back to Top]