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Article overview
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Discrete Versus Continuous Algorithms in Dynamics of Affective Decision Making | | V.I. Yukalov
; E.P. Yukalova
; | | Date: |
1 Sep 2023 | | Abstract: | The dynamics of affective decision making is considered for an intelligent
network composed of agents with different types of memory: long-term and
short-term memory. The consideration is based on probabilistic affective
decision theory, which takes into account the rational utility of alternatives
as well as the emotional alternative attractiveness. The objective of this
paper is the comparison of two multistep operational algorithms of the
intelligent network: one based on discrete dynamics and the other on continuous
dynamics. By means of numerical analysis, it is shown that, depending on the
network parameters, the characteristic probabilities for continuous and
discrete operations can exhibit either close or drastically different behavior.
Thus, depending on which algorithm is employed, either discrete or continuous,
theoretical predictions can be rather different, which does not allow for a
uniquely defined description of practical problems. This finding is important
for understanding which of the algorithms is more appropriate for the correct
analysis of decision-making tasks. A discussion is given, revealing that the
discrete operation seems to be more realistic for describing intelligent
networks as well as affective artificial intelligence. | | Source: | arXiv, 2309.00357 | | Services: | Forum | Review | PDF | Favorites | |
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