The Impact of Learning by Thought on Violations of Independence and Coalescing

Birnbaum, Michael H.; Schmidt, Ulrich

doi:10.1287/deca.2015.0316

Cited by 18 publications

(12 citation statements)

References 39 publications

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“…These reports indicate the need to assess the joint occurrence of the different choice paradoxes in a larger and more diverse set of lottery problems (for a similar point, see Birnbaum, 2008, p. 497). A recent study by Birnbaum and Schmidt (2015) showed a reduction in the occurrence of choice paradoxes among more experienced participants, a result that reinforces the need for further testing. Also relevant is a study by Erev et al (2017) attempting to jointly replicate a large number of established behavioral phenomena where notably, no event-splitting/coalescing effects were observed.…”

Section: Current State Of Affairsmentioning

confidence: 64%

Modeling choice paradoxes under risk: From prospect theories to sampling-based accounts

Kellen

Steiner

Davis‐Stober

et al. 2020

Cognitive Psychology

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Important developments in the study of decision making have been based on the establishment and testing of choice paradoxes (e.g., Allais') that reject different theories (e.g., Expected Utility Theory). One of the most popular and celebrated models in the literature, Cumulative Prospect Theory (CPT), has managed to retain its status despite a growing body of empirical evidence stemming from a collection of choice paradoxes that reject it. Two alternative models, Transfer of Attention Exchange (TAX) and an extension of Decision Field Theory (DFT e ), have been proposed as possible alternatives to CPT. To date, no study has directly compared these three models within the context of a large set of lottery problems that tests different choice paradoxes. The present study accomplishes this by using a large and diverse set of lottery problems, involving both potential gains and losses. Our results support the presence and robustness of a set of 'strong' choice paradoxes that reject CPT irrespective of its parametric form.Model comparison results show that DFT e provides the best account for the present set of lottery problems, as it is able to accommodate the choice data at large in a parsimonious fashion. The success of DFT e shows that many behavioral phenomena, including paradoxes that CPT cannot account for, can be successfully captured by a simple noisy-sampling process. Overall, our results suggest that researchers should move away from CPT, and focus their efforts on alternative models such as DFT e .

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Section: Current State Of Affairsmentioning

confidence: 64%

Modeling choice paradoxes under risk: From prospect theories to sampling-based accounts

Kellen

Steiner

Davis‐Stober

et al. 2020

Cognitive Psychology

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“…However, behaving fully optimally (on average) over time does not imply fully optimal behaviour at each time. Thus, non-standard decision-making theories seem to be most relevant only when the learning process has not been properly developed due to little experience with decisions (Birnbaum and Schmidt, 2015;Bonnefon and Sloman, 2013). Note that the theoretical assumptions presented in this paper may appear to be daunting.…”

Section: Discussionmentioning

confidence: 97%

Learning and Dynamic Choices Under Uncertainty: From Weighted Regret and Rejoice to Expected Utility

Zagonari

2016

SSRN Journal

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This paper identifies the globally stable conditions under which an individual facing the same choice in many subsequent times learns to behave as prescribed by the expected-utility model. To do so, the analysis moves from the relevant behavioural models suggested by psychology (i.e., weighted probabilities applied to regret and rejoice theory), and by updating probability estimations and outcome preferences according to the learning models suggested by neuroscience (i.e., adaptive learning aimed at reducing surprises), and analogous to Bayesian updating. The search context is derived from experimental economics, whereas the learning framework is borrowed from theoretical economics. Analytical results show that obstinate and lucky individuals are better off in the short-run (i.e., a low density of events in the reference period), but they do not learn, and this is true to a greater extent in a simple context; in contrast, reactive and unlucky individuals are worse off in the short-run, but they learn and are better off in the long-run (i.e., all individuals are equally lucky or unlucky), and this is true to a greater extent in a complex context. The expected-utility model explains real behaviours in the long-run whenever unlucky events are more likely than lucky events.

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“…However, behaving fully optimally (on average) over time does not imply fully optimal behaviour at any individual time. Thus, non‐standard decision‐making theories seem to be most relevant only when the learning process has not been properly developed due to little experience with decisions (Birnbaum & Schmidt, ; Bonnefon & Sloman, ).…”

Section: Discussionmentioning

confidence: 99%

Learning and dynamic choices under uncertainty: From weighted regret and rejoice to expected utility

Zagonari

2019

Manage Decis Econ

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This paper identifies the globally stable conditions under which an individual facing the same choice in many subsequent times learns to behave as prescribed by the expected‐utility model. The analysis moves from the relevant behavioural models suggested by psychology, by updating probability estimations and outcome preferences according to the learning models suggested by neuroscience, in a manner analogous to Bayesian updating. The search context is derived from experimental economics, whereas the learning framework is borrowed from theoretical economics. Analytical results show that the expected‐utility model explains real behaviours in the long run whenever bad events are more likely than good events.

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The Impact of Learning by Thought on Violations of Independence and Coalescing

Cited by 18 publications

References 39 publications

Modeling choice paradoxes under risk: From prospect theories to sampling-based accounts

Modeling choice paradoxes under risk: From prospect theories to sampling-based accounts

Learning and Dynamic Choices Under Uncertainty: From Weighted Regret and Rejoice to Expected Utility

Learning and dynamic choices under uncertainty: From weighted regret and rejoice to expected utility

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