Contingent gains and losses in a risk taking situation

Myers, Jerome L.; Suydam, Mary M.; Gambino, Blasé

doi:10.1037/e572342012-091

Cited by 11 publications

(38 citation statements)

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“…This is not really an assumption of the model but simply borrowed from other models of the phenomenon. However, it is noteworthy that the model can predict the result of this experiment even Table 3 Observed and Predicted Choice Proportions at Asymptote From Myers, Suydam, and Gambino (1965) though its basic choice rule obeys the property of independence between alternatives. The key to producing the result is that it was not the same rules (or indeed the same participants) that were choosing a gamble in the presence of a certain gain versus a certain loss or when the gamble was small versus when it was large.…”

Section: Choosing To Gamblementioning

confidence: 83%

“…In fact, we showed that the model adapts to both the means and the variabilities of rewards based on the scalar error signal. Last, the model exhibits the choice between certain and uncertain outcomes in Myers et al (1965). It also describes the risk-taking behavior that violated the independence axiom derived from the classic subjective utility theory.…”

Section: Summary Of Resultsmentioning

confidence: 99%

“…The property of independence states that if A (gamble with large magnitude) is chosen more often in the choice set containing A and C (the sure gain) than B (gamble with small magnitude) is chosen in the choice set containing B and C, then A should be chosen more often in the choice set containing A and D (the sure loss) than B is chosen in the choice set containing B and D. This property is true of our model, because if A is chosen more often in the presence of C than B is chosen in the presence of C, then A must have greater value than B, and this greater value should also lead to more choices in the presence of D. Nonetheless, as can be seen, our model predicts this effect in this experiment, and we explain why after describing the model. To model the data from Myers et al (1965), we assumed four choice productions. In the presence of a sure loss of 1 point, there was one pair of productions that chose the loss or the gamble.…”

Section: Choosing To Gamblementioning

confidence: 99%

“…Two of these theories are the decision field theory (DFT) of Busemeyer and Townsend (1993) and the proportional difference (PD) model of Gonzalez-Vallejo (2002). Although they are not restricted to models of recurrent choice, both of these models have provided good fits to the asymptotic performance of participants in the Myers and Suydam (1964) and Myers et al (1965) studies. However, instead of focusing on how preferences change with repeated feedback on previous choices, both theories focus on the local context defined by the alternatives in single-choice studies.…”

Section: Comparisons To Other Modelsmentioning

confidence: 99%

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From recurrent choice to skill learning: A reinforcement-learning model.

Anderson

2006

Journal of Experimental Psychology: General

121

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The authors propose a reinforcement-learning mechanism as a model for recurrent choice and extend it to account for skill learning. The model was inspired by recent research in neurophysiological studies of the basal ganglia and provides an integrated explanation of recurrent choice behavior and skill learning. The behavior includes effects of differential probabilities, magnitudes, variabilities, and delay of reinforcement. The model can also produce the violation of independence, preference reversals, and the goal gradient of reinforcement in maze learning. An experiment was conducted to study learning of action sequences in a multistep task. The fit of the model to the data demonstrated its ability to account for complex skill learning. The advantages of incorporating the mechanism into a larger cognitive architecture are discussed.

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Section: Choosing To Gamblementioning

confidence: 83%

Section: Summary Of Resultsmentioning

confidence: 99%

Section: Choosing To Gamblementioning

confidence: 99%

Section: Comparisons To Other Modelsmentioning

confidence: 99%

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From recurrent choice to skill learning: A reinforcement-learning model.

Anderson

2006

Journal of Experimental Psychology: General

121

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“…The evaluation of risks and risk-taking behavior also evidence negativity effects. The potential costs (negative attributes) are weighted more heavily than the potential rewards (positive attributes) of a given choice (Kogan & Wallach, 1967), a result that has been found in studies of subjects ranging from ethical risk-taking (Birnbaum, 1972;Rettig & Pasamanick, 1964;Rettig & Rawson, 1963;Rettig & Sinha, 1966) to gambling (Atthowe, 1960;Katz, 1964;Myers, Reilly, & Taub, 1961;Myers & Suydam, 1964;Myers, Suydam, & Gambino, 1965;Slovic & Lichtenstein, 1968). That negative information is weighted more heav-ily than comparable positive information when one forms an evaluation of social actors, objects, or events is well established.…”

Section: The Negativity Effect Description and Explanationmentioning

confidence: 92%

The Negativity Effect in Interaction It's All in Your Point of View

Kellermann

1989

Human Comm Res

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The negativity effect is defined as thedisproportionateweightingofnegative information in comparison to equidistantly rialenced positive information in the formation of judgments. The informativeness explanation ofthe negativity effect posits that the evaluative extremity (the distance from a psychological neutral point) and evaluative valence (positivelnegafiael of an event serve as determinants of its informativeness. Traditionally, this informativeness hypothesis explains the Occurrence of a negativity effect by presuming a skcwcd distribution with unequal tails for the frequency of outcomesfor valence; a mirror-image distribution for informativeness as afunction ofmlence; and a negative, linear relationship between typicality and informativeness. These three assumptions were tested directly in this research through thefitting of nonlinear equations. It was determined that (a) a negatively skewed distribution ofoutcomesfor valence does not occur in interaction contexts and that (b) typicality was a determinant ofinformativeness, although its importance as a determinant varies in response to whether one's perspective is that ofan observer or a participant. Thus, reliance on evaluative extremity and evaluative valence as determinants of informativeness was rejected; these variables are only descriptors when the distribution for the frequency of outcomesfor valence is skmed and has uneven tails.onversations contain information and are vehicles for information exchange (Kellermann, 1987). Conversations are C rich in their provisions of both content and relational information, although relatively little of the information available in the conversational stream is remembered by participants. Although the gist of conversations can be recognized at above chance levels

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Boundedly rational expected utility theory

et al. 2018

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We build a satisficing model of choice under risk which embeds Expected Utility Theory (EUT) into a boundedly rational deliberation process. The decision maker accumulates evidence for and against alternative options by repeatedly sampling from her underlying set of EU preferences until the evidence favouring one option satisfies her desired level of confidence. Despite its EUT core, the model produces patterns of behaviour that violate standard EUT axioms, while at the same time capturing systematic relationships between choice probabilities, response times and confidence judgments, which are beyond the scope of theories that do not take deliberation into account. Electronic supplementary material The online version of this article (10.1007/s11166-018-9293-3) contains supplementary material, which is available to authorized users.

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Contingent gains and losses in a risk taking situation

Cited by 11 publications

References 0 publications

From recurrent choice to skill learning: A reinforcement-learning model.

From recurrent choice to skill learning: A reinforcement-learning model.

The Negativity Effect in Interaction It's All in Your Point of View

Boundedly rational expected utility theory

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