Which one should I imitate?

Schlag, Karl H.

doi:10.1016/s0304-4068(97)00068-2

Cited by 154 publications

(101 citation statements)

References 7 publications

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“…This fact was previously only known for n = 1 and n = 2 (Schlag, 1998(Schlag, , 1999. Interestingly enough, the dynamics generated by SPOR n tends to Maynard Smith's adjusted replicator dynamics when the sample size n grows to infinity.…”

Section: Introductionmentioning

confidence: 68%

“…We restrict attention to individual behavior (what to play next) that is only a function of the information in the sample and of the own choice and payoff in the previous round. An example of such a behavioral rule is the sequentially evaluated Proportional Observation Rule (SPOR n , Schlag, 1999). Given this imitation rule, an individual considers each individual in his sample separately, switching to the strategy observed with a probability that is proportional to the observed payoff.…”

Section: Introductionmentioning

confidence: 99%

“…Given this imitation rule, an individual considers each individual in his sample separately, switching to the strategy observed with a probability that is proportional to the observed payoff. This seemingly unintuitive behavior, to ignore own payoff, is uniquely selected by Schlag (1999) who models optimal individual boundedly rational behavior. We review the underlying arguments from a new perspective in the appendix.…”

Section: Introductionmentioning

confidence: 99%

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Sophisticated imitation in cyclic games

Hofbauer¹,

Schlag²

2000

Journal of Evolutionary Economics

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Abstract. Individuals belonging to two large populations are repeatedly randomly matched to play a cyclic 2 × 2 game such as Matching Pennies. Between matching rounds, individuals sometimes change their strategy after observing a finite sample of other outcomes within their population. Individuals from the same population follow the same behavioral rule. In the resulting discrete time dynamics the unique Nash equilibrium is unstable. However, for sample sizes greater than one, we present an imitation rule where long run play cycles closely around the equilibrium.

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Section: Introductionmentioning

confidence: 68%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Sophisticated imitation in cyclic games

Hofbauer¹,

Schlag²

2000

Journal of Evolutionary Economics

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“…28 We estimated the full model by maximum-likelihood 29 and progressively obtained a more compact model regarding the random-effects through LR tests. 30 The random-slope variance was not significant for 'best response' at the 15% level in treatment 'incomplete' and even at the 40% level in treatment 'complete'. It was also not significant for 'imitate the best' at the 10% level and for 'follow the exemplary' at the 40% level.…”

Section: Individual Behaviormentioning

confidence: 87%

“…29 The model was estimated using GLLAMM (see Skrondal and Rabe-Hesketh, 2004). 30 Here the "naive" p-values are already corrected by division by two (see, e.g., Skrondal and Rabe-Hesketh 2004). 31 In both treatments subject-heteroskedastic level-1 variance (whose estimates are omitted for simplicity) was significant according to LR tests (p-value <0.000).…”

Section: [Table 8 About Here]mentioning

confidence: 99%

Subject-specific performance information can worsen the tragedy of the commons: Experimental evidence

Villena

Zecchetto

2011

Journal of Economic Psychology

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Evolutionary Dynamics of Strategies without Complete Information on Complex Networks

Zhang

2018

Asian Journal of Control

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As for the behaviors of multi-agent system, recent years have witnessed the growing interest in the study of cooperative behaviors by the aid of evolutionary game dynamics on complex networks. Thereinto, the updating rules deciding the evolution of strategies will significantly influence the steady state distribution of the system. The strategy updating rooted in the pursuit of larger benefits, will drive the system to evolve into the coexistence of different states or the domination by some strategies. To relax the often-used rules required explicit knowledge of the exact payoffs, this paper describes a new approach of updating strategy based on switching probabilities, which is independent on players' payoffs and degrees. And then the equilibrium state of the strategy evolution in the networks is studied. Our work here provides a computationally feasible way of estimating the steady characteristics of the strategy adoption of agents situating on complex networks. The stability analysis elucidates two important features: (i) the takeover of cooperation can be enhanced by the appropriate settings of the switching probabilities between strategies and (ii) larger average degree and power exponent in the employed scale-free network can make it easier for the coexistence of strategies. The results can help the design of initial strategy distribution of agents located on social networks to promote cooperation. Fig. 3. The steady states of the gaming system in the adopted BA scale-free network (the power-law exponent of scale-free network is 3), with the variation of the average degree n of the network. Here, n = 4, n = 6, n = 8, n = 10 are adopted for a comparison. is the probability of randomly connecting to D-players. Blue area: D strategy dominates the whole network.Red area: C strategy dominates the system. Other colors: The coexistence of the two strategies. Solid line: boundary lines of coexistence regions. [Color figure can be viewed at wileyonlinelibrary.com]

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Which one should I imitate?

Cited by 154 publications

References 7 publications

Sophisticated imitation in cyclic games

Sophisticated imitation in cyclic games

Subject-specific performance information can worsen the tragedy of the commons: Experimental evidence

Evolutionary Dynamics of Strategies without Complete Information on Complex Networks

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