Title
Probabilistic Dynamic Logic of Phenomena and Cognition
Document Type
Conference Proceeding
Department or Administrative Unit
Computer Science
Publication Date
7-18-2010
Abstract
The purpose of this paper is to develop further the main concepts of Phenomena Dynamic Logic (P-DL) and Cognitive Dynamic Logic (C-DL), presented in the previous paper. The specific character of these logics is in matching vagueness or fuzziness of similarity measures to the uncertainty of models. These logics are based on the following fundamental notions: generality relation, uncertainty relation, simplicity relation, similarity maximization problem with empirical content and enhancement (learning) operator. We develop these notions in terms of logic and probability and developed a Probabilistic Dynamic Logic of Phenomena and Cognition (P-DL-PC) that relates to the scope of probabilistic models of brain. In our research the effectiveness of suggested formalization is demonstrated by approximation of the expert model of breast cancer diagnostic decisions. The P-DL-PC logic was previously successfully applied to solving many practical tasks and also for modelling of some cognitive processes.
Recommended Citation
Vityaev, E., Kovalerchuk, B., Perlovsky, L., & Smerdov, S. (2010). Probabilistic Dynamic Logic of Phenomena and Cognition. The 2010 International Joint Conference on Neural Networks (IJCNN), 11593815. https://doi.org/10.1109/ijcnn.2010.5596833
Journal
The 2010 International Joint Conference on Neural Networks (IJCNN)
Rights
Copyright © 2010, IEEE
Comments
This article was originally published in The 2010 International Joint Conference on Neural Networks (IJCNN). The full-text article from the publisher can be found here.
Due to copyright restrictions, this article is not available for free download from ScholarWorks @ CWU.