DocumentCode
1716138
Title
Algorithmic and evolutionary game theory and their applications in Internet of Things
Author
Dae-Ki Kang
Author_Institution
Dongseo Univ., Busan, South Korea
fYear
2013
Firstpage
1
Lastpage
1
Abstract
Algorithmic game theory concerns algorithms and their analyses of finding equilibria in multi-agent strategic environments. Nash has shown that, in his seminal work, there is always an equilibrium where all agents can stay with their best responses. Evolutionary game theory concerns on stability and dynamics of agent population through differential reproduction governed by mutation and natural selection. Recently we have seen huge potentials of applying research achievements of algorithmic and evolutionary game theories to the domain of Internet of Things, which constitutes an intelligent network of humans, things and services.
Keywords
Internet of Things; evolutionary computation; game theory; multi-agent systems; Internet of Things; Nash equilibrium; agent population dynamics; agent population stability; algorithmic game theory; differential reproduction; evolutionary game theory; intelligent network; multiagent strategic environment; mutation; natural selection;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Communication Technology (ICACT), 2013 15th International Conference on
Conference_Location
PyeongChang
ISSN
1738-9445
Print_ISBN
978-1-4673-3148-7
Type
conf
Filename
6488125
Link To Document