Biological Regulation and Psychological Mechanisms Models of Adaptive Decision-Making Behaviors: Drives, Emotions, and Personality
The aim of this paper is to suggest a framework for adaptive agent decision-making modeling of biological regulation and psychological mechanisms. For this purpose, first, a perception-action cycle scheme for the agent-environment interactions and the deduced framework for adaptive agent decision-ma...
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Published in | Transactions on Computational Collective Intelligence XXIX Vol. 10840; pp. 69 - 83 |
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Main Authors | , |
Format | Book Chapter |
Language | English |
Published |
Switzerland
Springer International Publishing AG
2018
Springer International Publishing |
Series | Lecture Notes in Computer Science |
Subjects | |
Online Access | Get full text |
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Summary: | The aim of this paper is to suggest a framework for adaptive agent decision-making modeling of biological regulation and psychological mechanisms. For this purpose, first, a perception-action cycle scheme for the agent-environment interactions and the deduced framework for adaptive agent decision-making modeling are developed. Second, motivation systems: drives (homeostatic regulation), personality traits (five-factor model), and emotions (basic emotions) are developed. Third, a neural architecture implementation of the framework is suggested. Then, first tests related to a stimulation-drive (from a moving object), for two different agent personalities, and the activation level of emotions are presented and analyzed. Finally, a discussion is given in order to highlight important problems related to the adaptive decision-making behavior, the common currency that should have each system in the suggested framework, and the neural architecture, as well as to detail the ways they are solved. The obtained results demonstrate how the personality and emotion of the agent can be used to regulate the intensity of the interaction; predicting a promising result in future: to demonstrate how the nature of the interaction (stimulation-drive, social-drive, …) influences the agent behavior which could be very interesting for cooperative agents. |
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ISBN: | 3319902865 9783319902869 |
ISSN: | 0302-9743 1611-3349 |
DOI: | 10.1007/978-3-319-90287-6_4 |