Special Agents Can Promote Cooperation in the Population

被引:9
作者
Wang, Xin [1 ]
Han, Jing [1 ]
Han, Huawei [1 ]
机构
[1] Chinese Acad Sci, Inst Syst Sci, Key Lab Syst & Control, Acad Math & Syst Sci, Beijing, Peoples R China
来源
PLOS ONE | 2011年 / 6卷 / 12期
基金
中国国家自然科学基金;
关键词
TIT-FOR-TAT; EVOLUTIONARY GAMES; RECIPROCITY; EMERGENCE; ALTRUISM; AUTOMATA; STRATEGY;
D O I
10.1371/journal.pone.0029182
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Cooperation is ubiquitous in our real life but everyone would like to maximize her own profits. How does cooperation occur in the group of self-interested agents without centralized control? Furthermore, in a hostile scenario, for example, cooperation is unlikely to emerge. Is there any mechanism to promote cooperation if populations are given and play rules are not allowed to change? In this paper, numerical experiments show that complete population interaction is unfriendly to cooperation in the finite but end-unknown Repeated Prisoner's Dilemma (RPD). Then a mechanism called soft control is proposed to promote cooperation. According to the basic idea of soft control, a number of special agents are introduced to intervene in the evolution of cooperation. They comply with play rules in the original group so that they are always treated as normal agents. For our purpose, these special agents have their own strategies and share knowledge. The capability of the mechanism is studied under different settings. We find that soft control can promote cooperation and is robust to noise. Meanwhile simulation results demonstrate the applicability of the mechanism in other scenarios. Besides, the analytical proof also illustrates the effectiveness of soft control and validates simulation results. As a way of intervention in collective behaviors, soft control provides a possible direction for the study of reciprocal behaviors.
引用
收藏
页数:9
相关论文
共 66 条
[1]  
[Anonymous], J SYST SCI COMPLEXIT
[2]  
[Anonymous], 2006, EVOLUTIONARY DYNAMIC, DOI DOI 10.2307/J.CTVJGHW98
[3]   THE FURTHER EVOLUTION OF COOPERATION [J].
AXELROD, R ;
DION, D .
SCIENCE, 1988, 242 (4884) :1385-1390
[4]  
Axelrod R., 1984, EVOLUTION COOPERATIO
[5]  
AXTELL RL, RADICALS REVOLUTIONA
[6]   MODELING RATIONAL PLAYERS .1. [J].
BINMORE, K .
ECONOMICS AND PHILOSOPHY, 1987, 3 (02) :179-214
[7]   The evolution of strong reciprocity: cooperation in heterogeneous populations [J].
Bowles, S ;
Gintis, H .
THEORETICAL POPULATION BIOLOGY, 2004, 65 (01) :17-28
[8]   The evolution of altruistic punishment [J].
Boyd, R ;
Gintis, H ;
Bowles, S ;
Richerson, PJ .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2003, 100 (06) :3531-3535
[9]   On partially controlled multi-agent systems [J].
Brafman, RI ;
Tennenholtz, M .
JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH, 1996, 4 :477-507
[10]   Co-evolution of strategies and update rules in the prisoner's dilemma game on complex networks [J].
Cardillo, Alessio ;
Gomez-Gardenes, Jesus ;
Vilone, Daniele ;
Sanchez, Angel .
NEW JOURNAL OF PHYSICS, 2010, 12