Bio-inspired evolutionary computing with context-awareness and collective-effect

Yi Ting Chen, Jeng Shyang Pan, Shu Chuan Chu, Mong Fong Horng

    Research output: Contribution to journalArticlepeer-review


    In this study, an innovative conception is conceived to break the development bottleneck of the traditional ECs at present. This innovative conception is bio-inspired evolutionary computing with context-awareness and collective-effect called as Next-Generation ECs (EC 2.0). For the property of context-awareness in EC 2.0, the individuals are able to observe environmental information by physic property. And, the individual can regularly and closely move to objective. In addition, the individual behaviors in collective-effect include competition, cooperation and conflict. The conflict behaviors of individuals such as difference, contradiction or inconsistence are considered to design the search strategy. The proposed guidable bat algorithm (GBA) is the paradigm of EC 2.0. The bats governed by GBA are able to rapidly and precisely discover the global optimal solution. The simulation results show that the solving efficiency and solution quality of GBA are better than BA’s, even well-known HBA’s.

    Original languageEnglish
    Pages (from-to)99-113
    Number of pages15
    JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Publication statusPublished - 2014
    EventInternational Conference on Technologies and Applications of Artificial Intelligence - Taipei, Taiwan, Republic of China
    Duration: 21 Nov 201423 Nov 2014
    Conference number: 19th


    • Bio-inspired evolutionary computing
    • Collective-effect
    • Context-awareness
    • Guidable bat algorithm (GBA)
    • Next-generation evolutionary computing (EC 2.0)


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