Denotative and connotative management of uncertainty: A computational dual-process model
The interplay between intuitive and deliberative processing is known to be important for human decision making. As independent modes, intuitive processes can take on many forms from associative to constructive, while deliberative processes often rely on some notion of decision theoretic rationality...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Cambridge University Press
2021-03-01
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| Series: | Judgment and Decision Making |
| Subjects: | |
| Online Access: | http://journal.sjdm.org/20/200104/jdm200104.pdf |
| _version_ | 1797714751478824960 |
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| author | Jesse Hoey Neil J. MacKinnon Tobias Schröder |
| author_facet | Jesse Hoey Neil J. MacKinnon Tobias Schröder |
| author_sort | Jesse Hoey |
| collection | DOAJ |
| description | The interplay
between intuitive and deliberative processing is known to be important for
human decision making. As independent modes, intuitive processes can take on
many forms from associative to constructive, while deliberative processes often
rely on some notion of decision theoretic rationality or pattern matching. Dual
process models attempt to unify these two modes based on parallel constraint
networks or on socially or emotionally oriented adjustments to utility
functions. This paper presents a new kind of dual process model that unifies
decision theoretic deliberative reasoning with intuitive reasoning based on
shared cultural affective meanings in a single Bayesian sequential model.
Agents constructed according to this unified model are motivated by a
combination of affective alignment (intuitive) and decision theoretic reasoning
(deliberative), trading the two off as a function of the uncertainty or
unpredictability of the situation. The model also provides a theoretical bridge
between decision-making research and sociological symbolic interactionism.
Starting with a high-level view of existing models, we advance Bayesian Affect
Control Theory (BayesACT) as a promising new type of dual process model that
explicitly and optimally (in the Bayesian sense) trades off motivation, action,
beliefs and utility. We demonstrate a key component of the model as being
sufficient to account for some aspects of classic cognitive biases about
fairness and dissonance, and outline how this new theory relates to parallel
constraint satisfaction models. |
| first_indexed | 2024-03-12T07:56:49Z |
| format | Article |
| id | doaj.art-58b2a7d637a644629bed58cb403c607d |
| institution | Directory Open Access Journal |
| issn | 1930-2975 |
| language | English |
| last_indexed | 2024-03-12T07:56:49Z |
| publishDate | 2021-03-01 |
| publisher | Cambridge University Press |
| record_format | Article |
| series | Judgment and Decision Making |
| spelling | doaj.art-58b2a7d637a644629bed58cb403c607d2023-09-02T20:10:19ZengCambridge University PressJudgment and Decision Making1930-29752021-03-01162505550Denotative and connotative management of uncertainty: A computational dual-process modelJesse HoeyNeil J. MacKinnonTobias SchröderThe interplay between intuitive and deliberative processing is known to be important for human decision making. As independent modes, intuitive processes can take on many forms from associative to constructive, while deliberative processes often rely on some notion of decision theoretic rationality or pattern matching. Dual process models attempt to unify these two modes based on parallel constraint networks or on socially or emotionally oriented adjustments to utility functions. This paper presents a new kind of dual process model that unifies decision theoretic deliberative reasoning with intuitive reasoning based on shared cultural affective meanings in a single Bayesian sequential model. Agents constructed according to this unified model are motivated by a combination of affective alignment (intuitive) and decision theoretic reasoning (deliberative), trading the two off as a function of the uncertainty or unpredictability of the situation. The model also provides a theoretical bridge between decision-making research and sociological symbolic interactionism. Starting with a high-level view of existing models, we advance Bayesian Affect Control Theory (BayesACT) as a promising new type of dual process model that explicitly and optimally (in the Bayesian sense) trades off motivation, action, beliefs and utility. We demonstrate a key component of the model as being sufficient to account for some aspects of classic cognitive biases about fairness and dissonance, and outline how this new theory relates to parallel constraint satisfaction models.http://journal.sjdm.org/20/200104/jdm200104.pdfdual-process model emotion affect cognitive dissonance fairnessnakeywords |
| spellingShingle | Jesse Hoey Neil J. MacKinnon Tobias Schröder Denotative and connotative management of uncertainty: A computational dual-process model Judgment and Decision Making dual-process model emotion affect cognitive dissonance fairnessnakeywords |
| title | Denotative and
connotative management of uncertainty: A computational dual-process
model |
| title_full | Denotative and
connotative management of uncertainty: A computational dual-process
model |
| title_fullStr | Denotative and
connotative management of uncertainty: A computational dual-process
model |
| title_full_unstemmed | Denotative and
connotative management of uncertainty: A computational dual-process
model |
| title_short | Denotative and
connotative management of uncertainty: A computational dual-process
model |
| title_sort | denotative and connotative management of uncertainty a computational dual process model |
| topic | dual-process model emotion affect cognitive dissonance fairnessnakeywords |
| url | http://journal.sjdm.org/20/200104/jdm200104.pdf |
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