A dynamic model of social network formation.

By Brian Skyrms, Robin Pemantle. 2000

612 citations recorded by the source corpus.

We consider a dynamic social network model in which agents play repeated games in pairings determined by a stochastically evolving social network. Individual agents begin to interact at random, with the interactions modeled as games. The game payoffs determine which interactions are reinforced, and the network structure emerges as a consequence of the dynamics of the agents' learning behavior. We study this in a variety of game-theoretic conditions and show that the behavior is complex and sometimes dissimilar to behavior in the absence of structural dynamics. We argue that modeling network structure as dynamic increases realism without rendering the problem of analysis intractable.

Subfields: Management Science and Operations Research, Statistical and Nonlinear Physics

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Management Science and Operations Research

In Statistical and Nonlinear Physics

Citations in the corpus

Discovering Diverse Multi-Agent Strategic Behavior via Reward Randomization (2021, background): “…these algorithms can converge to when multiple NEs exist, e.g., the stag-hunt game and its variants, for which many learning dynamics fail to converge to a prevalence of the pure strategy Stag (Kandori et al., 1993; Ellison, 1993; Fang et al., 2002; Skyrms & Pemantle, 2009; Golman & Page, 2010)..”
The Stag Hunt and the Evolution of Social Structure (2003, background): “See Skyrms and Pemantle (2000), Theorem 3.”
Cooperation Prevails When Individuals Adjust Their Social Ties (2006, background): “with different co-evolutionary models, both in the context of the SH game [23], and in the context of the PD game [18,25],”
Evolutionary games on graphs (2006, background): “). Here we only focus on models where the growth and/or rewiring of the network is dictated by an evolutionary game played over the evolving social structure. Some early works on this subject include Skyrms and Pemantle (2000) who investigated various dynamic models of network formation assuming rei”
Games on graphs (2014, background): “tionships may change based on prior interactions [90], [23], [75], [74] reputations [25], or other factors [99], [98], [105], [119], [13].”
Reciprocal altruism and food sharing decisions among Hiwi and Ache hunter–gatherers (2004, positive): “Skyrms and Pemantle 2000 ), but can serve as a springboard for the construction of more realistic models.”
The Stag Hunt (2001, background): “19 Skyrms and Pemantle (2000).”
A survey of random processes with reinforcement (2006, background): “ro, so for suﬃciently large N, such an interval arises immediately. The issue of how people might come to choose the superior (a,a) in this case has been of longstanding concern to game theorists. In [SP00], a new evolutionary dynamic is introduced. A two-player game is ﬁxed, along with a population”
Social network theory: new insights and issues for behavioral ecologists (2009, background): “Social scientists have done some analyses combining game theory and SNT (Skyrms and Permantle 2000) built, for example, around the prisoner’s dilemma (Ebel and Bornoldt 2002; Zimmerman et al. 2004).”
The role of social networks in natural resource governance: What relational patterns make a difference? (2009, background): “…and simulations of various behavioral characteristics of individuals can provide important insights on how different networks structures can emerge, and how the emerging structures might co-evolve with behavioral changes of the individuals (cf. Hanaki et al., 2007; Skyrms and Pemantle, 2000).”
Opinion Dynamics and the Evolution of Social Power in Influence Networks (2015, background): “…literature features an accelerating number of proposals of dynamic models for (a) mechanisms of network formation and transformation (e.g., see [42] [68]) and (b) mechanisms by which individuals' attitudes, opinions and behaviors toward particular objects (specific issues, events, institutions,…”