Abstract
The paper is aimed at developing agent-based variants of traditional network models that make full use of concurrency. First, we review some classic models of the static structure of complex networks with the objective of developing agent-based models suited for simulating a large-scale, technology-enabled social network. Secondly, we outline the basic properties that characterize such networks. Then, we briefly discuss some classic network models and the properties of the networks they generate. Finally, we discuss how such models can be converted into agent-based models (i) to be executed more easily in heavily concurrent environments and (ii) to serve as basic blocks for more complex agent-based models. We evidence that many implicit assumptions made by traditional models regarding their execution environment are too expensive or outright impossible to maintain in concurrent environments. Consequently, we present the concurrency issues resulting from the violation of such assumptions. Then, we experimentally show that, under reasonable hypothesis, the agent-based variants maintain the main features of the classic models, notwithstanding the change of environment. Eventually, we present a meta-model that we singled out from the individual classic models and that we used to simplify the agent-oriented conversion of the traditional models. Finally, we discuss the software tools that we built to run the agent-based simulations.
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Agha G (1986) Actors: a model of concurrent computation in distributed systems. MIT Press, Cambridge
Albert R, Barabási AL (2002) Statistical mechanics of complex networks. Rev Mod Phys 74:47–74
Barabási AL, Albert R (1999) Emergence of scaling in random networks. Science 286:509–512
Bergenti F, Poggi A (2011) Building distributed and pervasive information management systems with HDS. In: Pallotta V, Soro A, Vargiu E (eds) Advances in distributed agent-based retrieval tools, Studies in computational intelligence. Springer, Berlin
Bergenti F, Franchi E, Poggi A (2010) Using HDS for realizing multiagent applications. In: Proceedings of the third international workshop on languages, methodologies and development tools for multi-agent systems (LADS’010), Lyon, France
Bergenti F, Franchi E, Poggi A (2011) Agent-based social networks for enterprise collaboration. In: 20th international workshops on enabling technologies: infrastructure for collaborative enterprises. IEEE, New York, pp 25–28
Bergenti F, Franchi E, Poggi A (2012) Enhancing social networks with agent and semantic web technologies. In: Brüggemann S, D’Amato C (eds) Collaboration and the semantic web: social networks, knowledge networks, and knowledge resources. IGI Global, Hershey, pp 83–100
Bollobás B, Chung FRK (1988) The diameter of a cycle plus a random matching. SIAM J Discrete Math 1(3):328–333
Bonabeau E (2002) Agent-based modeling: methods and techniques for simulating human systems. Proc Natl Acad Sci USA 99(Suppl 3):7280–7287
Clauset A, Shalizi C, Newman M (2009) Power-law distributions in empirical data. SIAM Rev 51(4):661–703
Cohen R, Havlin S (2003) Scale-free networks are ultrasmall. Phys Rev Lett 90(5):058701
Davidsen J, Ebel H, Bornholdt S (2002) Emergence of a small world from local interactions: modeling acquaintance networks. Phys Rev Lett 88(12):1–4
De Moura AL, Ierusalimschy R (2009) Revisiting coroutines. ACM Trans Program Lang Syst 31(2):6:1–6:31
Dymond PW, Cook SA (1980) Hardware complexity and parallel computation. In: IEEE annual symposium on foundations of computer science. IEEE Computer Society, Los Alamitos, pp 360–372
Epstein JM (1999) Agent-based computational models and generative social science. Complexity 4(5):41–60
Erdős P, Rényi A (1959) On random graphs. Publ Math 6(26):290–297
Franchi E (2012a) A domain specific language approach for agent-based social network modeling. In: International conference on advances in social network analysis and mining (ASONAM 2012), Istanbul, Turkey. IEEE Computer Society, Los Alamitos
Franchi E (2012b) Towards agent-based models for synthetic social network generation. In: Putnik GD, Cruz-Cunha MM (eds) Virtual and networked organizations, emergent technologies and tools, communications in computer and information science, vol 248. Springer, Berlin, pp 18–27
Franchi E, Poggi A (2011) Multi-agent systems and social networks. In: Cruz-Cunha M, Putnik GD, Lopes N, Gonçalves P, EM Miranda (eds) Business social networking: organizational, managerial, and technological dimensions. IGI Global, Hershey
Friborg RM, Bjørndalen J, Vinter B (2009) Three unique implementations of processes for PyCSP. In: Welch PH, Roebbers H, Broenink JF, Barnes FRM, Ritson CG, Sampson AT, Stiles GS, Vinter B (eds) Communicating process architectures 2009—WoTUG-32, Concurrent systems engineering, vol 67. IOS Press, Amsterdam, pp 277–293
Holme P, Kim B (2002) Growing scale-free networks with tunable clustering. Phys Rev E 65(2):2–5
Jackson M (2010) Social and economic networks. Princeton University Press, Princeton
Kumar R, Novak J, Tomkins A (2010) Structure and evolution of online social networks. In: Yu PSS, Han J, Faloutsos C (eds) Link mining: models, algorithms, and applications. Springer, New York, pp 337–357
Li X, Mao W, Zeng D, Wang FY (2008) Agent-based social simulation and modeling in social computing. In: Yang C, Chen H, Chau M, Chang K, Lang SD, Chen P, Hsieh R, Zeng D, Wang FY, Carley K, Mao W, Zhan J (eds) Intelligence and security informatics. Lecture notes in computer science, vol 5075. Springer, Berlin, pp 401–412
Luke S, Cioffi-Revilla C, Panait L, Sullivan K, Balan G (2005) Mason: a multiagent simulation environment. Simulation 81(7):517–527
Lytinen S, Railsback S (2012) The evolution of agent-based simulation platforms: a review of NetLogo 5.0 and ReLogo. In: Proceedings of the fourth international symposium on agent-based modeling and simulation, Vienna, Austria
Merton RK (1968) The Matthew effect in science. Science 169(3810):56–63
Minar N, Burkhart R, Langton C, Askenazi M (1996) The Swarm simulation system: a toolkit for building multi-agent simulations. Tech rep, Santa Fe Institute, Santa Fe
Newman MEJ (2000) Models of the small world. J Stat Phys 101(3):819–841
Newman MEJ (2003a) Properties of highly clustered networks. Phys Rev E 68:026121
Newman MEJ (2003b) The structure and function of complex networks. SIAM Rev 45(2):167–256
Newman MEJ, Watts DJ (1999) Renormalization group analysis of the small-world network model. Phys Lett A 263:341–346
North M, Howe T, Collier N, Vos J (2007) A declarative model assembly infrastructure for verification and validation. In: Advancing social simulation: the First World Congress. Springer, Berlin, pp 129–140
Pastor-Satorras R, Vespignani A (2001) Epidemic spreading in scale-free networks. Phys Rev Lett 86:3200–3203
Plotkin G (2004) A structural approach to operational semantics. J Log Algebr Program 60–61(0):17–139
Poggi A (2010) HDS: a software framework for the realization of pervasive applications. WSEAS Trans Comput 9(10):1149–1159
Price DDS (1976) A general theory of bibliometric and other cumulative advantage processes. J Am Soc Inf Sci 27(5):292–306
Simon HA (1955) On a class of skew distribution functions. Biometrika 42(3–4):425–440
Snijders TA (2011) Statistical models for social networks. Annu Rev Sociol 37(1):131–153
Szabó G, Alava M, Kertész J (2003) Structural transitions in scale-free networks. Phys Rev E 67(5):1–5
Tisue S, Wilensky U (2004) NetLogo: a simple environment for modeling complexity. In: International conference on complex systems, Boston, MA, pp 16–21
Watts DJ, Strogatz S (1998) Collective dynamics of small-world networks. Nature 393(6684):440–442
Yule GU (1925) A mathematical theory of evolution, based on the conclusions of Dr. J.C. Willis, F.R.S. Philos Trans R Soc Lond, B Contain Pap Biol Character 213(402–410):21–87
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Bergenti, F., Franchi, E. & Poggi, A. Agent-based interpretations of classic network models. Comput Math Organ Theory 19, 105–127 (2013). https://doi.org/10.1007/s10588-012-9150-x
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DOI: https://doi.org/10.1007/s10588-012-9150-x