ISJ Theoretical & Applied Science 08(64) 2018

Philadelphia, USA

Boldyrev PA, Krylov IB

THE ALGORITHM OF INDIVIDUAL LEARNING PATH CORRECTION IN INTELLIGENT MULTI-AGENT LEARNING SYSTEM.

Full Article: PDF

Scientific Object Identifier: http://s-o-i.org/1.1/TAS-08-64-10

DOI: https://dx.doi.org/10.15863/TAS.2018.08.64.10

Language: English

Citation: Boldyrev PA, Krylov IB (2018) THE ALGORITHM OF INDIVIDUAL LEARNING PATH CORRECTION IN INTELLIGENT MULTI-AGENT LEARNING SYSTEM. ISJ Theoretical & Applied Science, 08 (64): 58-61. Soi: http://s-o-i.org/1.1/TAS-08-64-10 Doi: https://dx.doi.org/10.15863/TAS.2018.08.64.10

Pages: 58-61

Published: 30.08.2018

Abstract: It was developed the algorithm of individual learning path correction. The algorithm of individual learning path correction involving Takagi-Sugeno-Kang fuzzy neural network includes the following operations: the determination of in-out variables; the choice of model out and rule base formation; the choice of fuzzification function and determination of learning curve parameters; the identification of learning curve elements to the fuzzy rules; fuzzification layer parameter setting; conclusion layer parameter setting. The algorithm allowed correct individual learning path at every step of work with the intelligent learning system in terms of learners’ special characteristics. The developed algorithm is software-based and successfully tested.

Key words: intelligent learning system, individual learning path, fuzzy neural network, multi-agent system.