Title :
Evolutionarily Stable Strategy of Networked Evolutionary Games
Author :
Daizhan Cheng ; Tingting Xu ; Hongsheng Qi
Author_Institution :
Sch. of Control Sci. & Eng., Shandong Univ., Jinan, China
Abstract :
The evolutionarily stable strategy (ESS) of networked evolutionary games (NEGs) is studied. Analyzing the ESS of infinite popular evolutionary games and comparing it with networked games, a new verifiable definition of ESS for NEGs is proposed. Then, the fundamental evolutionary equation (FEE) is investigated and used to construct the strategy profile dynamics (SPDs) of homogeneous NEGs. Two ways for verifying the ESS are proposed: 1) using the SPDs to verify it directly. The SPDs provides complete information about the NEGs, and then necessary and sufficient conditions are revealed. It can be used for NEGs with small size and 2) some sufficient conditions are proposed to verify the ESS of NEGs via their FEEs. This method is particularly suitable for large scale networks. Some illustrative examples are included to demonstrate the theoretical results.
Keywords :
evolutionary computation; game theory; ESS verification; FEE; SPDs; evolutionarily stable strategy; fundamental evolutionary equation; homogeneous NEGs; infinite popular evolutionary games; large scale networks; networked evolutionary games; strategy profile dynamics; sufficient conditions; Equations; Games; Mathematical model; Probabilistic logic; Sociology; Statistics; Vectors; Evolutionarily stable strategy (ESS); fundamental evolutionary equation (FEE); networked evolutionary game (NEG); semitensor product (STP) of matrices; semitensor product (STP) of matrices.;
Journal_Title :
Neural Networks and Learning Systems, IEEE Transactions on
DOI :
10.1109/TNNLS.2013.2293149