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Some Notes on Computational and Theoretical Issues in Artificial Intelligence and Machine Learning

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Advances in Neural Networks (WIRN 2015)

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Abstract

In the attempt to implement applications of public utility which simplify the user access to future, remote and nearby social services, new mathematical models and new psychological and computational approaches from existing cognitive frameworks and algorithmic solutions have been developed. The nature of these instruments is either deterministic, probabilistic, or both. Their use depends upon their contribute to the conception of new ICT functionalities and evaluation methods for modelling concepts of learning, reasoning, and data interpretation. This introductory chapter provide a brief overview on the theoretical and computational issues of such artificial intelligent methods and how they are applied to several research problems.

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Notes

  1. 1.

    NP-complete and NP-hard problems, where NP indicates that the problem has a Non Polynomial solution either in terms of computational time or of memory occupancy, or both.

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Esposito, A., Bassis, S., Morabito, F.C., Pasero, E. (2016). Some Notes on Computational and Theoretical Issues in Artificial Intelligence and Machine Learning. In: Bassis, S., Esposito, A., Morabito, F., Pasero, E. (eds) Advances in Neural Networks. WIRN 2015. Smart Innovation, Systems and Technologies, vol 54. Springer, Cham. https://doi.org/10.1007/978-3-319-33747-0_1

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  • DOI: https://doi.org/10.1007/978-3-319-33747-0_1

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