کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5499455 | 1533621 | 2017 | 5 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Historical payoff promotes cooperation in the prisoner's dilemma game
ترجمه فارسی عنوان
بازپرداخت تاریخی همکاری در بازی معضل زندانی را ترویج می دهد
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کلمات کلیدی
بازده تاریخی، همکاری، متقابل شبکه،
موضوعات مرتبط
مهندسی و علوم پایه
فیزیک و نجوم
فیزیک آماری و غیرخطی
چکیده انگلیسی
Understanding the evolution of cooperation among selfish individuals remains a large challenge. Network reciprocity has been proved to be an efficient way that can promote cooperation and has spawned many studies focused on network. Traditional evolutionary games on graph assumes players updating their strategies based on their current payoff, however, historical payoff may also play an indispensable role in agent's decision making processes. Another unavoidable fact in real word is that not all players can know exactly their historical payoff. Based on these considerations, in this paper, we introduce historical payoff and use a tunable parameter u to control the agent's fitness between her current payoff and historical payoff. When u equals to zero, it goes back to the traditional version; while positive u incorporates historical payoff. Besides, considering the limited knowledge of individuals, the structured population is divided into two types. Players of type A, whose proportion isâv, calculate their fitness using historical and current payoff. And for players of type B, whose proportion is1âv, their fitness is merely determined by their current payoff due to the limited knowledge. Besides, the proportion of these types keeps unchanged during the simulations. Through numerous simulations, we find that historical payoff can promote cooperation. When the contribution of historical payoff to the fitness is larger, the facilitating effect becomes more striking. Moreover, the larger the proportion of players of type A, the more obvious this promoting effect seems.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Chaos, Solitons & Fractals - Volume 104, November 2017, Pages 1-5
Journal: Chaos, Solitons & Fractals - Volume 104, November 2017, Pages 1-5
نویسندگان
Deng Zhenghong, Ma Chunmiao, Mao Xudong, Wang Shenglan, Niu Zhenxi, Gao Li,