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Influence of network topology on cooperative problem-solving systems

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Abstract

The idea of a collective intelligence behind the complex natural structures built by organisms suggests that the organization of social networks is selected so as to optimize problem-solving competence at the group level. Here we study the influence of the social network topology on the performance of a group of agents whose task is to locate the global maxima of NK fitness landscapes. Agents cooperate by broadcasting messages informing on their fitness and use this information to imitate the fittest agent in their influence networks. In the case those messages convey accurate information on the proximity of the solution (i.e., for smooth fitness landscapes), we find that high connectivity as well as centralization boosts the group performance. For rugged landscapes, however, these characteristics are beneficial for small groups only. For large groups, it is advantageous to slow down the information transmission through the network to avoid local maximum traps. Long-range links and modularity have marginal effects on the performance of the group, except for a very narrow region of the model parameters.

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References

  • Albert R, Barabási A-L (2002) Statistical mechanics of complex networks. Rev Mod Phys 74:47–97

    Article  Google Scholar 

  • Axelrod R (1984) The evolution of cooperation. Basic Books, New York

    Google Scholar 

  • Axelrod R (1997) The dissemination of culture: a model with local convergence and global polarization. J Confl Res 41:203–226

    Article  Google Scholar 

  • Barabási A-L, Albert R (1999) Emergence of scaling in random networks. Science 286:509–512

    Article  PubMed  Google Scholar 

  • Barabási A-L, Oltvai ZN (2004) Network biology: understanding the cell’s functional organization. Nat Rev Genet 5:101–113

    Article  PubMed  Google Scholar 

  • Barahona M, Pecora LM (2002) Synchronization in small-world systems. Phys Rev Lett 89:054101

    Article  PubMed  Google Scholar 

  • Barbosa LA, Fontanari JF (2009) Culture-area relation in Axelrod’s model for culture dissemination. Theor Biosci 128:205–210

    Article  Google Scholar 

  • Barrat A, Barthelemy M, Vespignani A (2008) Dynamical processes on complex networks. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • Bloom H (2001) Global brain: the evolution of mass mind from the big bang to the 21st century. Wiley, New York

    Google Scholar 

  • Bonabeau E, Dorigo M, Theraulaz G (1999) Swarm Intelligence: from natural to artificial systems. Oxford University Press, Oxford

    Google Scholar 

  • Clearwater SH, Huberman BA, Hogg T (1991) Cooperative solution of constraint satisfaction problems. Science 254:1181–1183

    Article  CAS  PubMed  Google Scholar 

  • Clune J, Mouret J-B, Lipson H (2013) The evolutionary origins of modularity. Proc R Soc B Biol Sci 280:20122863

    Article  Google Scholar 

  • Derex M, Beugin M-P, Godelle B, Raymond M (2013) Experimental evidence for the influence of group size on cultural complexity. Nature 503:389–391

    Article  CAS  PubMed  Google Scholar 

  • Derrida B (1981) Random-energy model: an exactly solvable model of disordered systems. Phys Rev B 24:2613–2626

    Article  CAS  Google Scholar 

  • Dunbar RIM (1992) Neocortex size as a constraint on group size in primates. J Hum Evol 22:469–493

    Article  Google Scholar 

  • Englemore R, Morgan T (1988) Blackboard Sys. Addison- Wesley, New York

    Google Scholar 

  • Fontanari JF (2010) Social interaction as a heuristic for combinatorial optimization problems. Phys Rev E 82:056118

    Article  Google Scholar 

  • Fontanari JF (2014) Imitative learning as a connector of collective brains. PLoS One 9:e110517

    Article  PubMed  PubMed Central  Google Scholar 

  • Fontanari JF (2015) Exploring NK fitness landscapes using imitative learning. Eur Phys J B 88:251

    Article  Google Scholar 

  • Garey MR, Johnson DS (1979) Computers and intractability: a guide to the theory of NP-completeness. Freeman, San Francisco

    Google Scholar 

  • Girvan M, Newman MEJ (2002) Community structure in social and biological networks. Proc Natl Acad Sci USA 99:7821–7826

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Gross T, Blasius B (2008) Adaptive coevolutionary networks: a review. J R Soc Interface 5:259–271

    Article  PubMed  Google Scholar 

  • Heyes CM (1994) Social learning in animals: categories and mechanisms. Biol Rev 69:207–231

    Article  CAS  PubMed  Google Scholar 

  • Hong L, Page SE (2004) Groups of diverse problem solvers can outperform groups of high-ability problem solvers. Proc Natl Acad Sci USA 101:16385–16389

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Huberman BA (1990) The performance of cooperative processes. Phys D 42:38–47

    Article  Google Scholar 

  • Kauffman S, Levin S (1987) Towards a general theory of adaptive walks on rugged landscapes. J Theor Biol 128:11–45

    Article  CAS  PubMed  Google Scholar 

  • Kaul H, Jacobson SH (2006) New global optima results for the Kauffman NK model: handling dependency. Math Program 108:475–494

    Article  Google Scholar 

  • Kennedy J (1998) Thinking is social: experiments with the adaptive culture model. J Confl Res 42:56–76

    Article  Google Scholar 

  • Kurvers RHJM, Krause J, Croft DP, Wilson ADM, Wolf M (2014) The evolutionary and ecological consequences of animal social networks: emerging issues. Trends Ecol Evol 29:326–335

    Article  PubMed  Google Scholar 

  • Laland KN, Atton N, Webster MM (2011) From fish to fashion: experimental and theoretical insights into the evolution of culture. Phil Trans R Soc B 366:958–968

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Laland KN, Williams K (1998) Social transmission of maladaptive information in the guppy. Behav Ecol 9:493–499

    Article  Google Scholar 

  • Moffett MW (2011) Adventures among ants: a global safari with a cast of trillions. University of California Press, Oakland

    Google Scholar 

  • Pasquaretta C, Levé M, Claidière N, van de Waal E, Whiten A, MacIntosh AJJ, Pelé M, Bergstrom ML, Borgeaud C, Brosnan SF, Crofoot MC, Fedigan LM, Fichtel C, Hopper LM, Mareno MC, Petit O, Schnoell AV, di Sorrentino EP, Thierry B, Tiddi B, Sueur C (2014) Social networks in primates: smart and tolerant species have more efficient networks. Sci Rep 4:7600

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Peres LR, Fontanari JF (2011) The media effect in Axelrod’s model explained. Europhys Lett 96:38004

    Article  Google Scholar 

  • Perra N, Gonçalves B, Pastor-Satorras R, Vespignani A (2012) Activity driven modeling of time varying networks. Sci Rep 2:469

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Queller DC, Strassmann JE (2009) Beyond society: the evolution of organismality. Philos Trans R Soc B 364:3143–3155

    Article  Google Scholar 

  • Rendell L, Boyd R, Cownden D, Enquist M, Eriksson K, Feldman MW, Fogarty L, Ghirlanda S, Lillicrap T, Laland KN (2010) Why copy others? Insights from the social learning strategies tournament. Science 328:208–213

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Saakian DB, Fontanari JF (2009) Evolutionary dynamics on rugged fitness landscapes: exact dynamics and information theoretical aspects. Phys Rev E 80:041903

    Article  Google Scholar 

  • Shibanai Y, Yasuno S, Ishiguro I (2001) Effects of global information feedback on diversity. J Confl Res 45:80–96

    Article  Google Scholar 

  • Solow D, Burnetas A, Tsai M, Greenspan NS (2000) On the expected performance of systems with complex interactions among components. Complex Sys 12:423–456

    Google Scholar 

  • Waters JS, Fewell JH (2012) Information processing in social insect networks. PLoS One 7:e40337

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Watts DJ, Strogatz SH (1998) Collective dynamics of ‘small-world’ networks. Nature 393:440–442

    Article  CAS  PubMed  Google Scholar 

  • Wilson E (1975) Sociobiology. Harvard University Press, Cambridge

    Google Scholar 

Download references

Acknowledgments

The research of JFF was partially supported by grant 2013/17131-0, São Paulo Research Foundation (FAPESP), and by grant 303979/2013-5, Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq). FAR acknowledges CNPq (grant 305940/2010-4) and FAPESP (grant 2013/26416-9) for financial support.

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Authors and Affiliations

  1. Instituto de Física de São Carlos, Universidade de São Paulo, Caixa Postal 369, 13560-970 São Carlos, São Paulo, Brazil

    José F. Fontanari

  2. Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo, Caixa Postal 668, 13560-970 São Carlos, São Paulo, Brazil

    Francisco A. Rodrigues

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  1. José F. Fontanari
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  2. Francisco A. Rodrigues
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Correspondence to José F. Fontanari.

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This article forms part of a special issue of Theory in Biosciences in commemoration of Olaf Breidbach.

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Fontanari, J.F., Rodrigues, F.A. Influence of network topology on cooperative problem-solving systems. Theory Biosci. 135, 101–110 (2016). https://doi.org/10.1007/s12064-015-0219-1

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