Towards Designing Linguistic Assessments Aggregation as a Distributed Neuroalgorithm

A challenging problem which arises in the domain of integrating symbolic and sub-symbolic computations within a massively parallel computational environments like Internet of Things is considered in application to the Linguistic Decision Making tasks. A novel theoretical idea is proposed on expressing linguistic operators in dynamics of an artificial neural network. The proposal consists of two consequent stages: expressing linguistic operators as structural manipulations and translating them in a neuroalgorithm. The theoretical foundation is Tensor Product Representation (TPR) that provides a generic framework of designing a neural network that does not require training and produces an exact result equivalent to the result of symbolic algorithms. This paper discusses viability of the proposed idea, demonstrates design of TPR-based arithmetic as a basic building block for construction of such a method and elaborates directions of further research.