Modeling habit patterns using conditional reflexes in agency
Tech Science Press
For decision-making and behavior dynamics in humans, the principal focus is on cognition. Cognition can be described using cognitive behavior, which has multiple states. This cognitive behavior can be incorporated with one of the internal mental states’ help, which includes desires, beliefs, emotions, intentions, different levels of knowledge, goals, skills, etc. That leads to habit development. Habits are highly refined patterns formed in the unconscious that evolve from conscious skill patterns in the human, and the same process can be implemented in the agency. These habit patterns are the outcomes of many internal values that may vary due to variations in parameter values forming these patterns. Fluctuations in the individual agent’s conditional reflexes may subject to strong habit patterns and leads to rationality. This paper presents the modeling of habit patterns in agency using conditional reflexes. Learning patterns, limited reflex patterns, skill patterns are working as main parameters for generating habit patterns. These input and output parameters will be validated using a scenario by applying fuzzy logic cascade techniques in which validation occurs at two levels. At the first level, conditional reflexes and initial patterns are applied, which form the output’s skill patterns. Then these skill patterns are interconnected with each other to form habit patterns. © 2021, Tech Science Press. All rights reserved.
This article is not available at CUD collection. The version of scholarly record of this article is published in Intelligent Automation and Soft Computing (2021), available online at: https://doi.org/10.32604/iasc.2021.018888
Agent’s behavior, Decision making, Habit, Human psychology, Rationality
Khan, Q., Ghazal, T. M., Abbas, S., Khan, W. A., Khan, M. A., Said, R. A., . . . Asif, M. (2021). Modeling habit patterns using conditional reflexes in agency. Intelligent Automation and Soft Computing, 30(2), 539-552. https://doi.org/10.32604/iasc.2021.018888