Effects of Neighbourhood Structure on Evolution of Cooperation in N-Player Iterated Prisoner’s Dilemma

Chiong, Raymond; Dhakal, Sandeep; Jankovic, Ljubomir

doi:10.1007/978-3-540-77226-2_95

Cited by 12 publications

(8 citation statements)

References 9 publications

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“…In other versions of NIPD, players act on a lattice or arranged along a ring, and a player's behaviour depends on previous actions of the neighbours and if a neighbour has higher pay off, it may adopt its strategy (e.g. [21,38]). By contrast, in our model, interactions happen between two individuals, and in each interaction cost is paid only by the actor and benefit is received only by the receiver.…”

Section: Discussionmentioning

confidence: 99%

Cooperation among non-relatives evolves by state-dependent generalized reciprocity

et al. 2010

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For decades, attempts to understand cooperation between non-kin have generated substantial theoretical and empirical interest in the evolutionary mechanisms of reciprocal altruism. There is growing evidence that the cognitive limitations of animals can hinder direct and indirect reciprocity because the necessary mental capacity is costly. Here, we show that cooperation can evolve by generalized reciprocity (help anyone, if helped by someone) even in large groups, if individuals base their decision to cooperate on a state variable updated by the outcome of the last interaction with an anonymous partner. We demonstrate that this alternative mechanism emerges through small evolutionary steps under a wide range of conditions. Since this state-based generalized reciprocity works without advanced cognitive abilities it may help to understand the evolution of complex social behaviour in a wide range of organisms.

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Section: Discussionmentioning

confidence: 99%

Cooperation among non-relatives evolves by state-dependent generalized reciprocity

et al. 2010

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“…A simple extension to the IPD, which we refer to as the N-IPD game (see [4,7,8,9,11,43]), is to modify the game so that multiple players play a version of the game at the same time. In the N-IPD, N players repeatedly interact with one another (where N > 2), making decisions independently based on two actions -cooperate or defect -without knowing the choices of other players.…”

Section: Iterated N-player Gamesmentioning

confidence: 99%

Iterated n-player games on small-world networks

Chiong

Kirley

2011

Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation

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The evolution of strategies in iterated multi-player social dilemma games is studied on small-world networks. Two different games with varying reward values -the N-player Iterated Prisoner's Dilemma (N-IPD) and the N-player Iterated Snowdrift game (N-ISD) -form the basis of this study. Here, the agents playing the game are mapped to the nodes of different network architectures, ranging from regular lattices to small-world networks and random graphs. In a given game instance, the focal agent participates in an iterative game with N − 1 other agents drawn from its local neighbourhood. We use a genetic algorithm with synchronous updating to evolve agent strategies. Extensive Monte Carlo simulation experiments show that for smaller cost-to-benefit ratios, the extent of cooperation in both games decreases as the probability of re-wiring increases. For higher cost-tobenefit ratios, when the re-wiring probability is small we observe an increase in the level of cooperation in the N-IPD population, but not the N-ISD population. This suggests that the small-world network structure with small re-wiring probabilities can both promote and maintain higher levels of cooperation when the game becomes more challenging.

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“…Numerous studies in the EGT literature have demonstrated that by restricting the interactions of players to local neighbourhoods/groups (Chiong, Dhakal, & Jankovic, 2007;Chiong & Kirley, 2009, 2011, 2012aKillingback & Doebeli, 1996;Nowak & May, 1992, 1993 or subdividing the population into groups (Killingback, Bieri, & Flatt,, 2006;Nunney, 1985;Traulsen & Nowak, 2006;Wilson 1990), cooperative behaviour can be promoted. Motivated by this, we hope to apply principles and findings from EGT to address issues in online study groups.…”

Section: Evolutionary Game Theorymentioning

confidence: 99%

Collaborative Learning in Online Study Groups: An Evolutionary Game Theory Perspective

Chiong¹,

Jovanović

2012

JITE:Research

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Executive SummaryEducational benefits of online collaborative group work have been confirmed in numerous research studies. Most frequently cited advantages include the development of skills of critical thinking and problem solving as well as skills of self-reflection and co-construction of knowledge and meaning. However, the establishment and maintenance of active collaboration in online study groups is a challenging task, primarily due to students' inability (e.g., owing to time constraints or lack of collaboration skills) or reluctance (e.g., due to the lack of or low participation of other group members) to participate actively in the group work. Aiming to better understand and contribute to the resolution of the problems of effective online group work, we followed a novel approach based on Evolutionary Game Theory (EGT). While EGT has been used extensively as a framework for studying the emergence and maintenance of cooperation in many disciplines, to the best of our knowledge, it has not yet been applied to understanding and facilitating group collaboration in online learning settings. In this paper, we present a study we have conducted in order to investigate whether, and to what extent, EGT can be applied to explain students' participation in collaborative study groups.

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Effects of Neighbourhood Structure on Evolution of Cooperation in N-Player Iterated Prisoner’s Dilemma

Cited by 12 publications

References 9 publications

Cooperation among non-relatives evolves by state-dependent generalized reciprocity

Cooperation among non-relatives evolves by state-dependent generalized reciprocity

Iterated n-player games on small-world networks

Collaborative Learning in Online Study Groups: An Evolutionary Game Theory Perspective

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