Unifying Genetic and Game Theoretic Models of Kin Selection for Continuous Traits

1998 ◽  
Vol 194 (3) ◽  
pp. 391-407 ◽  
Author(s):  
Troy Day ◽  
Peter D. Taylor
Keyword(s):  
Kin Selection ◽  
Game Theoretic ◽  
Selection For ◽  
Continuous Traits

scholarly journals Sex differences in helping effort reveal the effect of future reproduction on cooperative behaviour in birds

2018 ◽  
Vol 285 (1885) ◽  
pp. 20181164 ◽  
Author(s):  
Philip A. Downing ◽  
Ashleigh S. Griffin ◽  
Charlie K. Cornwallis
Keyword(s):  
Sex Differences ◽  
Reproductive Success ◽  
Kin Selection ◽  
Cooperative Behaviour ◽  
The Future ◽  
Helping Behaviour ◽  
Future Reproduction ◽  
Selection For ◽  
Family Groups

The evolution of helping behaviour in species that breed cooperatively in family groups is typically attributed to kin selection alone. However, in many species, helpers go on to inherit breeding positions in their natal groups, but the extent to which this contributes to selection for helping is unclear as the future reproductive success of helpers is often unknown. To quantify the role of future reproduction in the evolution of helping, we compared the helping effort of female and male retained offspring across cooperative birds. The kin selected benefits of helping are equivalent between female and male helpers—they are equally related to the younger siblings they help raise—but the future reproductive benefits of helping differ because of sex differences in the likelihood of breeding in the natal group. We found that the sex which is more likely to breed in its natal group invests more in helping, suggesting that in addition to kin selection, helping in family groups is shaped by future reproduction.

Kin Selection for Ground Squirrel Alarm Calls

1977 ◽  
Vol 111 (980) ◽  
pp. 782-785 ◽  
Author(s):  
Christopher Dunford
Keyword(s):  
Kin Selection ◽  
Ground Squirrel ◽  
Alarm Calls ◽  
Selection For

scholarly journals Distributed Demand-Aware Channel-Slot Selection for Multi-UAV Networks: A Game-Theoretic Learning Approach

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 14799-14811 ◽  
Author(s):  
Jiaxin Chen ◽  
Qihui Wu ◽  
Yuhua Xu ◽  
Yuli Zhang ◽  
Yang Yang
Keyword(s):  
Learning Approach ◽  
Game Theoretic ◽  
Selection For ◽  
Multi Uav
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