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NeuroSymbolic integration with uncertainty

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Abstract

Most of the tasks which require intelligent behavior have some degree of uncertainty associated with them. The occurrence of uncertainty might be because of several reasons such as the incomplete domain knowledge, unreliable or ambiguous data due to measurement errors, inconsistent data representation. Most of the knowledge-based systems require the incorporation of some form of uncertainty management, in order to handle this kind of indeterminacy present in the system. In this paper, we present one such method to handle the uncertainty in neurules, a neuro-symbolic integration concept. Neuro-Computing is used within the symbolic frame work for improving the performance of symbolic rules. The uncertainty, the personal belief degree that an uncertain event may occur is managed by computing the composite belief values of incomplete or conflicting data. With the implementation of uncertainty management in neurules, the accuracy of the inference mechanism and the generalization performance can be improved.

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Acknowledgements

The authors would like to thank Prof. Pushpak Bhattacharyya, Prof. D. Malathi for his support and guidance during this work. The authors would like to thank Department of Science & Technology, Govt. of India for providing fund under Woman Scientist Scheme (WOS-A) with the project code-SR/WOS-A/ET/1075/2014.

Funding

This work is funded by Department of Science & Technology, Govt. of India under Woman Scientist Scheme (WOS-A) with the project code-SR/WOS-A/ET/1075/2014.

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  1. Department of Computer Science & Engineering, Indian Institute of Technology Bombay, Mumbai, 400076, India

    Sreelekha S.

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S., S. NeuroSymbolic integration with uncertainty. Ann Math Artif Intell 84, 201–220 (2018). https://doi.org/10.1007/s10472-018-9605-y

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