Paper Info
Title
Studying bio-inspired coalition formation of robots for detecting intrusions using game theory.
Abstract
In this paper, inspired by the society of animals, we study the coalition formation of robots for detecting intrusions using game theory. We consider coalition formation in a group of three robots that detect and capture intrusions in a closed curve loop. In our analytical model, individuals seek alliances if they think that their detect regions are too short to gain an intrusion capturing probability larger than their own. We assume that coalition seeking has an investment cost and that the formation of a coalition determines the outcomes of parities, with the detect length of a coalition simply being the sum of those of separate coalition members. We derive that, for any cost, always detecting alone is an evolutionarily stable strategy (ESS), and that, if the cost is below a threshold, always trying to form a coalition is an ESS (thus a three-way coalition arises).
Year
DOI
Venue
2010
10.1109/TSMCB.2009.2034976
IEEE Transactions on Systems, Man, and Cybernetics, Part B
Keywords
Field
DocType
intrusion detection,bio-inspired,three-way coalition,bio-inspired coalition formation,robots,coalition formation,mobile sensors,multi-robot systems,investment cost,analytical model,game theory,evolutionarily stable strategy,bioinspired coalition formation,closed curve loop,coalition,separate coalition member,security of data,mobile robots,biomimetics,investments,computer simulation,robotics,algorithms,collaboration
Evolutionarily stable strategy,Intrusion,Computer science,Investment cost,Artificial intelligence,Game theory,Robot,Intrusion detection system,Mobile robot,Core (game theory)
Journal
Volume
Issue
ISSN
40
3
1941-0492
Citations 
PageRank 
References 
21
1.03
7
Authors
2
Name
Order
Citations
PageRank
Xiannuan Liang1907.37
Yang Xiao26317456.36