Topology selection for multi-agent systems with opposite leaders

2016 ◽  
Vol 93 ◽  
pp. 43-49 ◽  
Author(s):  
Jingying Ma ◽  
Yuanshi Zheng ◽  
Long Wang
2018 ◽  
Vol 83 ◽  
pp. 149-161 ◽  
Author(s):  
Fatemeh Golpayegani ◽  
Zahra Sahaf ◽  
Ivana Dusparic ◽  
Siobhán Clarke

2020 ◽  
Vol 34 (05) ◽  
pp. 7047-7054 ◽  
Author(s):  
Nicolas Anastassacos ◽  
Stephen Hailes ◽  
Mirco Musolesi

Social dilemmas have been widely studied to explain how humans are able to cooperate in society. Considerable effort has been invested in designing artificial agents for social dilemmas that incorporate explicit agent motivations that are chosen to favor coordinated or cooperative responses. The prevalence of this general approach points towards the importance of achieving an understanding of both an agent's internal design and external environment dynamics that facilitate cooperative behavior. In this paper, we investigate how partner selection can promote cooperative behavior between agents who are trained to maximize a purely selfish objective function. Our experiments reveal that agents trained with this dynamic learn a strategy that retaliates against defectors while promoting cooperation with other agents resulting in a prosocial society.


2014 ◽  
Vol 47 (3) ◽  
pp. 11697-11702 ◽  
Author(s):  
Wen Yang ◽  
Xiaofan Wang ◽  
Hongbo Shi

Sign in / Sign up

Export Citation Format

Share Document