A study on like-attracts-like versus elitist selection criterion for human-like social behavior of memetic mulitagent systems

Xuefeng Chen, Yifeng Zeng, Yew-Soon Ong, Choon Sing Ho, Yanping Xiang

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    Abstract

    Memetic multiagent system emerges as an enhanced version of multiagent systems with the implementation of meme inspired computational agents. It aims to evolve human-like behavior of multiple agents by exploiting the Dawkins’ notion of a meme and Universal Darwinism. Previous research has developed a computational framework in which a series of memetic operations have been designed for implementing human-like agents. This paper will focus on improving the human-like behavior of multiple agents when they are engaged in social interactions. The improvement is mainly on how an agent shall learn from others and adapt its behavior in a complex dynamic environment. In particular, we design a new mechanism that supervises how the agent shall select one of the other agents for the learning purpose. The selection is a trade-off between the elitist and like-attracts-like principles. We demonstrate the desirable interactions of multiple agents in two problem domains.
    Original languageEnglish
    Number of pages8
    Publication statusPublished - 2013
    EventIEEE Congress on Evolutionary Computation - Fiesta Americana Grand Coral Beach Hotel, Cancun, Mexico
    Duration: 20 Jun 201323 Jun 2013

    Conference

    ConferenceIEEE Congress on Evolutionary Computation
    CountryMexico
    CityCancun
    Period20/06/1323/06/13

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    Chen, X., Zeng, Y., Ong, Y-S., Sing Ho, C., & Xiang, Y. (2013). A study on like-attracts-like versus elitist selection criterion for human-like social behavior of memetic mulitagent systems. Paper presented at IEEE Congress on Evolutionary Computation, Cancun, Mexico.