Learning, Local Interaction, and Coordination

By Glenn Ellison. 1993

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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)..”
Maximizing the spread of influence through a social network (2003, methodology): “Using an analysis framework based on submodular functions, we show that a natural greedy strategy obtains a solution that is provably within 63% of optimal for several classes of models; our framework suggests a general approach for reasoning about the performance guarantees of algorithms for…”
Networks in Finance (2008, background): “1 A spatial avor has been introduced to motivate why agents do not interact with all the other agents in the economy simultaneously, but only with their neighbors in a network (see Durlauf, 1996; Ellison, 1993; Benabou, 1993, 1996).”
On the formation of interaction networks in social coordination games (2002, background): “The unique stochastically stable state will be all players playing A as shown by Ellison (1993), and as he shows this result also holds for some more general neighborhood structures on circles.”
The Evolution of Social and Economic Networks (2002, background): “Dutta and Mutuswami [1997] discuss alternative approaches that capture coalitional deviations.”
Correcting for missing data in information cascades (2011, background): “Why estimate properties of complete cascades? Processes that form cascades in a social network have been studied in a number of domains, including the diffusion of medical and technological innovations [22], adoption of strategies in game-theoretic settings [6], product adoption, promotion, and vira”
Heterogeneity and Uniqueness in Interaction Games (2003, background): “In a local interaction setting, a number of papers have shown that local interaction allows the risk dominant action to spread contagiously by best response dynamics alone (e.g., Blume (1995) and Ellison (1993)).”
The Impact of Information Provision on Agglomeration Bonus Performance: An Experimental Study on Local Networks (2014, unknown): “This result corresponds to theoretical evidence on contagion of risk dominant choices on local networks provided by both Ellison (1993) and Weidenholzer (2010) and experimental evidence recorded in Keser, Ehrhart, and Berninghaus (1998) and Berninghaus, Ehrhart, and Keser (2002).”
A survey of random processes with reinforcement (2006, background): “m, does not have time to learn the better equilibrium. This many simultaneous mutations are as rare as all the oxygen molecules suddenly moving to the other side of the room (well not quite). Ellison [Ell93] proposes a variant. Let the agents be labeled by the integers modulo N, and for ﬁxed k < ”
A Dynamic Model of Network Formation (2001, background): “Finally, in evolutionary game theory, Ellison 1993 , Ž .”
A dynamic model of social network formation. (2000, background): “ble, whether repeated interactions can be expected to converge to equilibrium, and if so, how quickly convergence takes place (14).”