Self-questioning games and ping-pong effect in the BA network

Gao, Kun; Wang, Wen-Xu; Wang, Bing–Hong

doi:10.1016/j.physa.2007.02.086

Cited by 29 publications

(25 citation statements)

References 17 publications

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“…Compared with the previous work in this field [32,47], our version of the self-questioning mechanism showed clear advantages in (re)establishing and sustaining symmetrical cooperative behavior. However, we found that the cooperation promoting effects of the implemented updating rule were not robust enough under noisy conditions.…”

Section: Discussionmentioning

confidence: 75%

“…A player i obtains a payoff V i = V i /4 by interacting with its four outward-linked neighbours, where V i is obtained by summing up the payoffs of all outward-linked neighbors. Subsequently, by means of self-questioning in a virtual game [32,47], each player adopts its anti-strategy and estimates a virtual payoff V v = V v /4, where V v is obtained by summing up the virtual payoffs of all the outward-linked neighbors. By comparing the virtual payoff with the real payoff, players can estimate their optimal strategy corresponding to the highest payoff and realize whether their current strategy is of any advantage [47].…”

Section: Modelmentioning

confidence: 99%

“…A special attention is given to an alternative strategy updating rule, the so-called self-questioning mechanism [32,47], and its influence on cooperative behavior under noisy conditions.…”

Section: Introductionmentioning

confidence: 99%

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Cooperation in the snowdrift game on directed small-world networks under self-questioning and noisy conditions

Qiu

Hadzibeganovic

Chen

et al. 2010

Computer Physics Communications

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Cooperation in the evolutionary snowdrift game with a self-questioning updating mechanism is studied on annealed and quenched small-world networks with directed couplings. Around the payoff parameter value r = 0.5, we find a size-invariant symmetrical cooperation effect. While generally suppressing cooperation for r > 0.5 payoffs, rewired networks facilitated cooperative behavior for r < 0.5. Fair amounts of noise were found to break the observed symmetry and further weaken cooperation at relatively large values of r. However, in the absence of noise, the self-questioning mechanism recovers symmetrical behavior and elevates altruism even under large-reward conditions. Our results suggest that an updating mechanism of this type is necessary to stabilize cooperation in a spatially structured environment which is otherwise detrimental to cooperative behavior, especially at high costto-benefit ratios. Additionally, we employ component and local stability analyses to better understand the nature of the manifested dynamics.

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Section: Discussionmentioning

confidence: 75%

Section: Modelmentioning

confidence: 99%

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Cooperation in the snowdrift game on directed small-world networks under self-questioning and noisy conditions

Qiu

Hadzibeganovic

Chen

et al. 2010

Computer Physics Communications

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“…The deterministic rule be proposed by Nowak and May, 5 the stochastic evolutionary rule be introduced by Szab o and T€ oke 4 are used commonly. Apart from these, learning theory has provided a reasonable framework to study the evolutionary games, since individuals could be viewed as adaptive agents, hence, they can adopt a self-questioning mechanism [13][14][15]53 and assess the relative e±ciency of the strategy, via data envelopment analysis (DEA). 16 Moreover, individuals can update their strategies according to the di®erence between the actual and aspiration payo® based on learning theory.…”

Section: Introductionmentioning

confidence: 99%

Effects of aspiration-induced adaptation and migration on the evolution of cooperation

Wang

et al. 2014

Int. J. Mod. Phys. C

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In the light of the prospect theory (PT), we study the prisoner's dilemma game (PDG) on square lattice by integrating the deterministic and Data envelopment analysis (DEA) e±cient rule into adaptive rules: the individual will change evolutionary rule and migrate if its payo® is lower than their aspiration levels. Whether the individual choose to change the evolutionary rule and migrate is determined by the relation between its payo® and aspiration level. The results show that the cooperation frequency can hold unchange with the increasing of temptation to defect. The individual chooses to adopt DEA e±cient rule and to migrate that can induce the emergence of cooperation as the payo® is lower than its aspiration.

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“…On the one hand, such framework has been widely used to depict the frequency-dependent genetic evolution of microbial communities or other animal populations, such as the Moran process [10] and the Wright-Fisher process [11]. On the other hand, evolutionary game dynamics has been used to interpret culture evolution in humans, which contains pairwise comparison process [1], [12], [13] and a kind of non-imitation learning process, namely self-learning process [14]- [16].…”

Section: Introductionmentioning

confidence: 99%

Evolutionary game dynamics of multi-agent cooperation driven by self-learning

Wang

2013

2013 9th Asian Control Conference (ASCC)

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Multi-agent cooperation problem is a fundamental issue in the coordination control field. Individuals achieve a common task through association with others or division of labor. Evolutionary game dynamics offers a basic framework to investigate how agents self-adaptively switch their strategies in accordance with various targets, and also the evolution of their behaviors. In this paper, we analytically study the strategy evolution in a multiple player game model driven by self-learning. Self-learning dynamics is of importance for agent strategy updating yet seldom analytically addressed before. It is based on self-evaluation, which applies to distributed control. We focus on the abundance of different strategies (behaviors of agents) and their oscillation (frequency of behavior switching). We arrive at the condition under which a strategy is more abundant over the other under weak selection limit. Such condition holds for any finite population size of ≥ 3, thus it fits for the systems with finite agents, which has notable advantage over that of pairwise comparison process. At certain states of evolutionary stable state, there exists "ping-pong effect" with stable frequency, which is not affected by aspirations. Our results indicate that self-learning dynamics of multi-player games has special characters. Compared with pairwise comparison dynamics and Moran process, it shows different effect on strategy evolution, such as promoting cooperation in collective risk games with large threshold.

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Self-questioning games and ping-pong effect in the BA network

Cited by 29 publications

References 17 publications

Cooperation in the snowdrift game on directed small-world networks under self-questioning and noisy conditions

Cooperation in the snowdrift game on directed small-world networks under self-questioning and noisy conditions

Effects of aspiration-induced adaptation and migration on the evolution of cooperation

Evolutionary game dynamics of multi-agent cooperation driven by self-learning

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