Abstract
In this paper, random-opposition-based learning (ROBL) is proposed. ROBL is a generalized version of opposition-based learning (OBL). ROBL introduces randomness in OBL. ROBL is applied for some metaheuristics and artificial neural network. The examples are provided with preliminary results.
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Bairathi, D., Gopalani, D. (2020). Random-opposition-based Learning for Computational Intelligence. In: Tuba, M., Akashe, S., Joshi, A. (eds) Information and Communication Technology for Sustainable Development. Advances in Intelligent Systems and Computing, vol 933. Springer, Singapore. https://doi.org/10.1007/978-981-13-7166-0_11
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DOI: https://doi.org/10.1007/978-981-13-7166-0_11
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