An evaluation and comparison of models of risky intertemporal choice.

Luckman, Ashley; Donkin, Chris; Newell, Ben R.

doi:10.1037/rev0000223

Cited by 18 publications

(23 citation statements)

References 60 publications

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“…Importantly, we modeled the delay to the larger reward with a transition probability and used the MDP, a utility based model, to compute action values when the transition probabilities were higher than expected (certain environment) and lower than expected (uncertain environment), which made the TD simulations risky intertemporal choices. We found that impulsive agents performed worse when transition probabilities to larger, delayed rewards were higher than expected, similar to previous findings using probabilistic future rewards (for reviews, see [ 61 , 62 ]). However, when the transition probabilities to delayed rewards in the environment were lower than expected, the impulsive agent with the lower discount factor collected more average reward than the non-impulsive agent that chose larger, future rewards that were not delivered.…”

Section: Discussionsupporting

confidence: 90%

“…It remains an open debate whether attribute-comparison (i.e. time vs. time and probability vs. probability) or utility based models are more appropriate for capturing intertermporal choice behavior and neural representation, and there are many kinds of intertemporal choices based on combinations of attributes [ 62 ]. Here we demonstrate an example where an impulsive agent can perform better than a non-impulsive agent, and this example could be extended to other kinds of intertemporal choices by using mismatched expectations across a range of attributes.…”

Section: Discussionmentioning

confidence: 99%

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Environmental uncertainty and the advantage of impulsive choice strategies

Burk

Averbeck

2023

PLoS Comput Biol

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Choice impulsivity is characterized by the choice of immediate, smaller reward options over future, larger reward options, and is often thought to be associated with negative life outcomes. However, some environments make future rewards more uncertain, and in these environments impulsive choices can be beneficial. Here we examined the conditions under which impulsive vs. non-impulsive decision strategies would be advantageous. We used Markov Decision Processes (MDPs) to model three common decision-making tasks: Temporal Discounting, Information Sampling, and an Explore-Exploit task. We manipulated environmental variables to create circumstances where future outcomes were relatively uncertain. We then manipulated the discount factor of an MDP agent, which affects the value of immediate versus future rewards, to model impulsive and non-impulsive behavior. This allowed us to examine the performance of impulsive and non-impulsive agents in more or less predictable environments. In Temporal Discounting, we manipulated the transition probability to delayed rewards and found that the agent with the lower discount factor (i.e. the impulsive agent) collected more average reward than the agent with a higher discount factor (the non-impulsive agent) by selecting immediate reward options when the probability of receiving the future reward was low. In the Information Sampling task, we manipulated the amount of information obtained with each sample. When sampling led to small information gains, the impulsive MDP agent collected more average reward than the non-impulsive agent. Third, in the Explore-Exploit task, we manipulated the substitution rate for novel options. When the substitution rate was high, the impulsive agent again performed better than the non-impulsive agent, as it explored the novel options less and instead exploited options with known reward values. The results of these analyses show that impulsivity can be advantageous in environments that are unexpectedly uncertain.

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Section: Discussionsupporting

confidence: 90%

Section: Discussionmentioning

confidence: 99%

Environmental uncertainty and the advantage of impulsive choice strategies

Burk

Averbeck

2023

PLoS Comput Biol

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“…Our focus on the motivations and processes underlying people’s withdrawal decision permits an opportunity to go beyond these descriptive results and speculate on their potential implications for understanding how and why people arrived at their decision. Multiple studies of the psychology of human judgment and decision-making have proven the difficulties some people have in understanding exponential growth and in overcoming present bias (e.g., Luckman et al, 2020 , McKenzie and Liersch, 2011 , Soll et al, 2013 ;), that combine to make the offer of immediately available large sums of money very tempting ( Argento et al, 2015 , Munnell and Webb, 2022 ). We found that many people made the decision to withdraw almost immediately, and did not, or could not, estimate the impact of the transfer on their longer-term retirement savings.…”

Section: Discussionmentioning

confidence: 99%

Determinants of early-access to retirement savings: Lessons from the COVID-19 pandemic

Bateman¹,

Dobrescu²,

Liu³

et al. 2023

The Journal of the Economics of Ageing

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“…Equations 25 and 26 encompass the special cases, as well the case where goods are both delayed and probabilistic. The only other successful general model of risky intertemporal choice is the RITCH model (Luckman et al, 2020).…”

Section: Variations On Rachlin's Themesmentioning

confidence: 99%

Variations on a theme by Rachlin: Probability discounting

Killeen

2022

J Exper Analysis Behavior

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Rachlin and colleagues laid the groundwork for treating the discounting of probabilistic goods as a variant of the discounting of delayed goods. This approach was seminal for a large body of subsequent research. The present paper finds the original development problematic: In converting probability to delay, the authors incorrectly dropped trial duration. The subsumption of probability by delay is also empirically questionable, as those are different functions of variables such as magnitude of outcome and commodity versus money. A variant of Rachlin's theme treats human discounting studies as psychophysical matching experiments, in which one compound stimulus is adjusted to equal another. It is assumed that a function of amount (its utility) is multiplied by a function of probability (its weight).Conjoint measurement establishes the nature of these functions, yielding a logarithmic transform on amount, and a Prelec function on probability. This model provides a good and parsimonious account of probability discounting in diverse data sets. Variant representations of the data are explored. By inserting the probabilistically discounted utility into the additive utility theory of delay discounting, a general theory of probabilistic intertemporal choice is achieved.

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An evaluation and comparison of models of risky intertemporal choice.

Abstract: Please refer to published version for the most recent bibliographic citation information. If a published version is known of, the repository item page linked to above, will contain details on accessing it.

Cited by 18 publications

References 60 publications

Environmental uncertainty and the advantage of impulsive choice strategies

Environmental uncertainty and the advantage of impulsive choice strategies

Determinants of early-access to retirement savings: Lessons from the COVID-19 pandemic

Variations on a theme by Rachlin: Probability discounting

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