ICTACT Journal on Soft Computing

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Computational Model for Mental Factor Classification


Affiliations
1 School of Computer Sciences, KBC North Maharashtra University, India
     

   Subscribe/Renew Journal


Artificial Wisdom is advancement of Artificial Intelligence where wisdom should be recognized with the intelligence. Wisdom can be realized by adding values in the positive decisions. This is resulted in to the overall behavior of human being. Behavior can be demonstrated with the help of simulating thought process. Thoughts are generated in the mind along with the mental state. Mental state also known as mental factor is responsible for arousal of different types of thoughts. Ancient Indian cannon Abhidhamm claimed 52 mental factors. These are categorized in three classes such as Ethically Variable Factor, Unwholesome Factor and Beautiful Factor. Proposed computational model of consciousness demonstrates the classification of the mental states. Dataset consists of 445 samples collected from various respondents by asking three questions. Preprocessing is performed by using the techniques of Natural language processing and non-axiomatic logic. Convolutional Neural Network Machine learning technique applied to classify the mental factors. Performance of the proposed system is measured by applying statistical measures such as Accuracy, Precision, Specificity, Recall and F1-Score. Accuracy for small and large database is obtained as 86.92% and 93.02% respectively.

Keywords

Cognitive Science, Artificial Wisdom, Thought Generation, Consciousness, Mental Factors
Subscription Login to verify subscription
User
Notifications
Font Size

  • D. Jeste, S. Graham and Ho-Cheol Kim, “Beyond Artificial Intelligence: Exploring Artificial Wisdom”, International Psychogeriatrics Vol. 32, pp. 993-1001, 2020.

  • Robert Siegler and Roberto Araya, “A Computational Model of Conscious and Unconscious Strategy Discovery”, Advances in Child Development and Behavior, Vol. 33, pp. 1-42, 2005.

  • K. Tavakolian and S. Rezaei, “Mental Task Classification for Brain Computer Interface Applications”, Proceedings of 1st Canadian Student Conference on Biomedical Computing, pp. 1-6, 2006.

  • Janusz Starzyk and Dilip Prasad, “A Computational Model of Machine Consciousness”, International Journal of Machine Consciousness, Vol. 3, No. 2, pp. 1-26, 2010.

  • S.N. Nallaperuma and A.S. Karunananda, “EME: An Emergent Model of Emotions”, Proceedings of International Conference on Advances in ICT for Emerging Regions, pp. 19-25, 2011.

  • Shivani Poddar, Sindhu Kiranmai Ernala and Navjyoti Singh, “PACMAN: Psycho and Computational Framework of an Individual (Man)”, Proceedings of International Conference on Emotion and Sentiment Analysis, pp. 10-17, 2016.

  • Eric Lou, “A Novel Computer Simulation of the Mind using Buddhist Theories”, Available at http://dx.doi.org/10.2139/ssrn.3026291, Accessed at 2021.

  • Artemy A. Kotov, “A Computational Model of Consciousness for Artificial Emotional Agents”, Psychology in Russia: State of the Art, Vol. 10, No. 3, pp. 57-73, 2017.

  • Romi Banerjee and Sankar K. Pal, “A Computational Model for the Endogenous Arousal of Thoughts Through Z*-Numbers”, Information Sciences, Vol. 405, pp. 227-258, 2017.

  • J.H. Van Hateren, “A Theory of Consciousness: Computation, Algorithm, and Neurobiological Realization”, Biological Cybernetics, Vol. 113, No. 4, pp. 357–372, 2019.

  • Pei Wang, “Non-Axiomatic Logic: A Model of Intelligent Reasoning”, World Scientific Book Publisher, 2012.

  • R. Yamashita, M. Nishio and R.K.G. Do, “Convolutional Neural Networks: An Overview and Application in Radiology”, Insights Imaging, Vol. 23, pp. 611-629, 2018.


Abstract Views: 66

PDF Views: 2




  • Computational Model for Mental Factor Classification

Abstract Views: 66  |  PDF Views: 2

Authors

R. J. Ramteke
School of Computer Sciences, KBC North Maharashtra University, India
S. S. Gharde
School of Computer Sciences, KBC North Maharashtra University, India

Abstract


Artificial Wisdom is advancement of Artificial Intelligence where wisdom should be recognized with the intelligence. Wisdom can be realized by adding values in the positive decisions. This is resulted in to the overall behavior of human being. Behavior can be demonstrated with the help of simulating thought process. Thoughts are generated in the mind along with the mental state. Mental state also known as mental factor is responsible for arousal of different types of thoughts. Ancient Indian cannon Abhidhamm claimed 52 mental factors. These are categorized in three classes such as Ethically Variable Factor, Unwholesome Factor and Beautiful Factor. Proposed computational model of consciousness demonstrates the classification of the mental states. Dataset consists of 445 samples collected from various respondents by asking three questions. Preprocessing is performed by using the techniques of Natural language processing and non-axiomatic logic. Convolutional Neural Network Machine learning technique applied to classify the mental factors. Performance of the proposed system is measured by applying statistical measures such as Accuracy, Precision, Specificity, Recall and F1-Score. Accuracy for small and large database is obtained as 86.92% and 93.02% respectively.

Keywords


Cognitive Science, Artificial Wisdom, Thought Generation, Consciousness, Mental Factors

References