Experimenting with Acquisition of and Matching to Systemic Classifiers
DOI:
https://doi.org/10.51408/1963-0026Keywords:
Systemic Classifiers, Matching, Chess, RGT, Cognitive Systems, AcquisitionAbstract
We are modeling acquisition and classification abilities for the machine. The research line we follow, is based on the ideas of inventors of algorithms letting constructively model human computations and on some extension of those ideas aimed to model constructively other mental doings [1, 2]. We question the issues of acquisition of and matching to systemic classifiers and experimenting to prove the adequacy of our models. We experiment in the frame of RGT class of combinatorial problems for a RGT kernel problem, chess.
References
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E. Pogossian, “On the way to dominating cognition”, Transactions of IIAP NAS RA, Mathematical Problems of Computer Sciences, vol. 48, pp. 79-91, 2018.
S. Grigoryan, N. Hakobyan and H.Vrtanesyan “Object–oriented modeling of matching to systemic classifiers”, Transactions of IIAP NAS RA Mathematical Problems of Computer Sciences, vol. 48. pp. 115-121, 2018.
E. Pogossian, “Effectiveness enhancing knowledge-based strategies for SSRGT class of defense problems”, NATO ASI 2011 Prediction and Recognition of Piracy Efforts Using Collaborative Human-Centric Information Systems, Salamanca, Spain, p. 16, 2011.
S. Grigoryan “Research and Development of Algorithms and Programs of KnowledgeAcquisition and Their Effective Application to Resistance Problems”, Ph.D., p 111, Yerevan, Armenia, 2016.
E. Pogossian, “Adaptation of combinatorial algorithms”, Academy of Sci. of Armenia, p.293, 1983, Yerevan
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