The Beneficial Role of Mobility for the Emergence of Innovation

Innovation is a key ingredient for the evolution of several systems, including social and biological ones. Focused investigations and lateral thinking may lead to innovation, as well as serendipity and other random discovery processes. Some individuals are talented at proposing innovation (say innovators), while others at deeply exploring proposed novelties, at getting further insights on a theory, or at developing products, services, and so on (say developers). This separation in terms of innovators and developers raises an issue of paramount importance: under which conditions a system is able to maintain innovators? According to a simple model, this work investigates the evolutionary dynamics that characterize the emergence of innovation. In particular, we consider a population of innovators and developers, in which agents form small groups whose composition is crucial for their payoff. The latter depends on the heterogeneity of the formed groups, on the amount of innovators they include, and on an award-factor that represents the policy of the system for promoting innovation. Under the hypothesis that a “mobility” effect may support the emergence of innovation, we compare the equilibria reached by our population in different cases. Results confirm the beneficial role of “mobility”, and the emergence of further interesting phenomena.

[1]  Alessandro Bessi,et al.  Personality traits and echo chambers on facebook , 2016, Comput. Hum. Behav..

[2]  Attila Szolnoki,et al.  Reward and cooperation in the spatial public goods game , 2010, ArXiv.

[3]  Stefan Thurner,et al.  Schumpeterian economic dynamics as a quantifiable model of evolution , 2009, 0909.3482.

[4]  James A. Tebbe Where Good Ideas Come From: The Natural History of Innovation , 2011 .

[5]  Guorong Wu,et al.  Information Flow in Networks and the Law of Diminishing Marginal Returns: Evidence from Modeling and Human Electroencephalographic Recordings , 2012, PloS one.

[6]  Long Wang,et al.  Partner selections in public goods games with constant group size. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.

[7]  S. Strogatz,et al.  Dynamics on Expanding Spaces: Modeling the Emergence of Novelties , 2017, 1701.00994.

[8]  Ernesto Estrada,et al.  The Structure of Complex Networks: Theory and Applications , 2011 .

[9]  M. Nowak,et al.  Evolutionary games and spatial chaos , 1992, Nature.

[10]  Maxi San Miguel,et al.  Social and strategic imitation: the way to consensus , 2012, Scientific Reports.

[11]  J. Gómez-Gardeñes,et al.  Evolutionary game dynamics in a growing structured population , 2009, 0907.2649.

[12]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[13]  Attila Szolnoki,et al.  Cooperation driven by success-driven group formation , 2016, Physical review. E.

[14]  Nicola Perra,et al.  Social Phenomena: From Data Analysis to Models , 2015 .

[15]  Attila Szolnoki,et al.  Evolutionary dynamics of group interactions on structured populations: a review , 2013, Journal of The Royal Society Interface.

[16]  A. Barabasi,et al.  Quantifying the evolution of individual scientific impact , 2016, Science.

[17]  Alessandro Vespignani,et al.  Towards a Characterization of Behavior-Disease Models , 2011, PloS one.

[18]  Vittorio Loreto,et al.  The dynamics of correlated novelties , 2013, Scientific Reports.

[19]  G. Caldarelli,et al.  Systemic risk in financial networks , 2013 .

[20]  Federico Battiston,et al.  The role of noise in the spatial public goods game , 2016, 1605.08690.

[21]  E. Rogers,et al.  Diffusion of innovations , 1964, Encyclopedia of Sport Management.

[22]  Mark E. J. Newman,et al.  The Structure and Function of Complex Networks , 2003, SIAM Rev..

[23]  Julia Poncela-Casasnovas,et al.  Adoption of a High-Impact Innovation in a Homogeneous Population. , 2014, Physical review. X.

[24]  Arthur O. Eger,et al.  Technological Innovation as an Evolutionary Process , 2018 .

[25]  Attila Szolnoki,et al.  Topology-independent impact of noise on cooperation in spatial public goods games. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.

[26]  Sergi Valverde,et al.  Major transitions in information technology , 2016, Philosophical Transactions of the Royal Society B: Biological Sciences.

[27]  Attila Szolnoki,et al.  Selection of noise level in strategy adoption for spatial social dilemmas. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.

[28]  Peter Tschmuck,et al.  Creativity and innovation in the music industry , 2006 .

[29]  Stephen Shennan,et al.  Innovation in cultural systems : contributions from evolutionary anthropology , 2009 .

[30]  Ricard V. Solé,et al.  The evolutionary ecology of technological innovations , 2013, Complex..

[31]  Samuel Madden,et al.  From Databases to Big Data , 2012, IEEE Internet Comput..

[32]  Marco Alberto Javarone Competitive dynamics of lexical innovations in multi-layer networks , 2013, ArXiv.

[33]  R. Solé,et al.  Evolving protein interaction networks through gene duplication. , 2003, Journal of theoretical biology.

[34]  Jean-Daniel Zucker,et al.  From Individual Choice to Group Decision Making , 2000 .

[35]  Jure Leskovec,et al.  Predicting positive and negative links in online social networks , 2010, WWW '10.

[36]  Albert-László Barabási,et al.  Statistical mechanics of complex networks , 2001, ArXiv.

[37]  Iztok Fister,et al.  Toward the Discovery of Citation Cartels in Citation Networks , 2016, Front. Phys..

[38]  O. Sporns,et al.  Complex brain networks: graph theoretical analysis of structural and functional systems , 2009, Nature Reviews Neuroscience.

[39]  Daniele Marinazzo,et al.  Evolutionary dynamics of group formation , 2016, PloS one.

[40]  Marjan Mernik,et al.  Exploration and exploitation in evolutionary algorithms: A survey , 2013, CSUR.

[41]  Guido Caldarelli,et al.  Scale-Free Networks , 2007 .

[42]  A. Barra,et al.  Emerging Heterogeneities in Italian Customs and Comparison with Nearby Countries , 2015, PloS one.

[43]  Steven Johnson,et al.  Where Good Ideas Come From , 2010 .

[44]  Marco Tomassini,et al.  Random diffusion and cooperation in continuous two-dimensional space. , 2014, Journal of theoretical biology.

[45]  Vito Latora,et al.  Emergence of Multiplex Communities in Collaboration Networks , 2015, PloS one.

[46]  Ray Bert,et al.  \IWhere Good Ideas Come From: The Natural History of Innovation\N By Steven Johnson. New York City: Riverhead Books, 2010. , 2010 .

[47]  M. Perc,et al.  Social diversity and promotion of cooperation in the spatial prisoner's dilemma game. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[48]  F. C. Santos,et al.  Social diversity promotes the emergence of cooperation in public goods games , 2008, Nature.

[49]  CrepinsekMatej,et al.  Exploration and exploitation in evolutionary algorithms , 2013 .

[50]  Dyson Freeman,et al.  Birds and Frogs , 2009 .

[51]  Charu C. Aggarwal,et al.  Co-author Relationship Prediction in Heterogeneous Bibliographic Networks , 2011, 2011 International Conference on Advances in Social Networks Analysis and Mining.

[52]  Matjaž Perc,et al.  Stochastic win-stay-lose-shift strategy with dynamic aspirations in evolutionary social dilemmas. , 2016, Physical review. E.

[53]  Steven Johnson Steven Johnson: Where good ideas come from , 2010 .

[54]  Giuliano Armano,et al.  Emergence of acronyms in a community of language users , 2013 .

[55]  Sandy L. Zabell,et al.  Inventing New Signals , 2012, Dyn. Games Appl..

[56]  J. Cuesta,et al.  Heterogeneous networks do not promote cooperation when humans play a Prisoner’s Dilemma , 2012, Proceedings of the National Academy of Sciences.

[57]  F. C. Santos,et al.  Scale-free networks provide a unifying framework for the emergence of cooperation. , 2005, Physical review letters.

[58]  Tobias Galla,et al.  Stochastic evolution in populations of ideas , 2016, Scientific Reports.

[59]  Vittorio Loreto,et al.  Journal of Statistical Mechanics: An IOP and SISSA journal Theory and Experiment Sharp transition towardsshared vocabularies in multi-agent systems , 2006 .

[60]  Matjaz Perc,et al.  Collective behavior and evolutionary games - An introduction , 2013, 1306.2296.

[61]  B. Tether Who co-operates for innovation, and why: An empirical analysis , 2002 .

[62]  Luciano Pietronero,et al.  From Innovation to Diversification: A Simple Competitive Model , 2015, PloS one.

[63]  Christopher McCarty,et al.  Predicting author h-index using characteristics of the co-author network , 2013, Scientometrics.

[64]  Attila Szolnoki,et al.  Ordering in spatial evolutionary games for pairwise collective strategy updates. , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.

[65]  Thomas W. Valente Network models of the diffusion of innovations , 1996, Comput. Math. Organ. Theory.

[66]  S. Galam,et al.  Towards a theory of collective phenomena: Consensus and attitude changes in groups , 1991 .

[67]  K. Laland,et al.  Animal innovation: An introduction. , 2003 .

[68]  Chao Wang,et al.  Imitating emotions instead of strategies in spatial games elevates social welfare , 2011, 1109.1712.

[69]  M. Nowak Five Rules for the Evolution of Cooperation , 2006, Science.

[70]  M. Perc,et al.  Group-Size Effects on the Evolution of Cooperation in the Spatial Public Goods Game , 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.

[71]  M. Nowak Evolutionary Dynamics: Exploring the Equations of Life , 2006 .

[72]  Elena Agliari,et al.  A statistical mechanics approach to Granovetter theory , 2010, ArXiv.

[73]  E. M.,et al.  Statistical Mechanics , 2021, Manual for Theoretical Chemistry.