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A self-adaptive strategy for evolution of cooperation in distributed networks

Journal Article


Abstract


  • This paper studies the phenomenon of the evolution

    of cooperation in distributed networks by using an iterated game.

    An iterated game in a distributed network is a multiple round

    game, where in each round, a player gains a payoff by playing

    a game with its neighbours and updates its action based on the

    actions and/or payoffs of its neighbours. The interaction model

    between players is usually represented as a two-player, two-action

    (namely cooperation and defection) Prisoner’s Dilemma game

    (which is a prototypical model for interaction between selfish

    individuals). Many researchers have developed strategies (also

    called update rules) for the evolution of cooperation in distributed

    networks in order to enhance cooperation, i.e., to increase the

    proportion of cooperators. Experimental results reported in the

    current literature, however, have demonstrated that each of these

    strategies has both advantages and disadvantages. In this paper, a

    self-adaptive strategy is proposed for the evolution of cooperation

    in distributed networks, which can utilise the strengths and

    avoid the limitations of existing strategies. Moreover, we have

    a theoretical finding about the final proportion of cooperators,

    evolved by any pure (or deterministic) strategies, in four types

    of a game. This finding is independent of the initial proportion

    of cooperators, the topology of the network (e.g., a small-world

    network or a scale-free network), and the specific game (e.g., the

    Prisoner’s Dilemma game or the Snow Drift game).

Publication Date


  • 2015

Citation


  • Ye, D. & Zhang, M. (2015). A self-adaptive strategy for evolution of cooperation in distributed networks. IEEE Transactions on Computers, 64 (4), 899-911.

Scopus Eid


  • 2-s2.0-84925061025

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/5052

Has Global Citation Frequency


Number Of Pages


  • 12

Start Page


  • 899

End Page


  • 911

Volume


  • 64

Issue


  • 4

Place Of Publication


  • United States

Abstract


  • This paper studies the phenomenon of the evolution

    of cooperation in distributed networks by using an iterated game.

    An iterated game in a distributed network is a multiple round

    game, where in each round, a player gains a payoff by playing

    a game with its neighbours and updates its action based on the

    actions and/or payoffs of its neighbours. The interaction model

    between players is usually represented as a two-player, two-action

    (namely cooperation and defection) Prisoner’s Dilemma game

    (which is a prototypical model for interaction between selfish

    individuals). Many researchers have developed strategies (also

    called update rules) for the evolution of cooperation in distributed

    networks in order to enhance cooperation, i.e., to increase the

    proportion of cooperators. Experimental results reported in the

    current literature, however, have demonstrated that each of these

    strategies has both advantages and disadvantages. In this paper, a

    self-adaptive strategy is proposed for the evolution of cooperation

    in distributed networks, which can utilise the strengths and

    avoid the limitations of existing strategies. Moreover, we have

    a theoretical finding about the final proportion of cooperators,

    evolved by any pure (or deterministic) strategies, in four types

    of a game. This finding is independent of the initial proportion

    of cooperators, the topology of the network (e.g., a small-world

    network or a scale-free network), and the specific game (e.g., the

    Prisoner’s Dilemma game or the Snow Drift game).

Publication Date


  • 2015

Citation


  • Ye, D. & Zhang, M. (2015). A self-adaptive strategy for evolution of cooperation in distributed networks. IEEE Transactions on Computers, 64 (4), 899-911.

Scopus Eid


  • 2-s2.0-84925061025

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/5052

Has Global Citation Frequency


Number Of Pages


  • 12

Start Page


  • 899

End Page


  • 911

Volume


  • 64

Issue


  • 4

Place Of Publication


  • United States