Observed Variability and Values Matter: Toward a Better Understanding of Information Search and Decisions from Experience

Mehlhorn, Katja; Ben-Asher, Noam; Dutt, Varun; González, Cleotilde

doi:10.1002/bdm.1809

Cited by 15 publications

(19 citation statements)

References 53 publications

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“…In most real-life situations, rewards tend to also provide the agent with information about the quality of the selected option (Gupta et al, 2006) and hence the distribution of rewards available. In some situations, agents might receive information about foregone payoffs in non-selected alternatives (Yechiam & Busemeyer, 2006); and, even when no material rewards are obtained during exploration in a given situation, information search in itself can be rewarding if it delivers positive experiences (Denrell & Le Mens, 2011;Gonzalez & Dutt, 2012;Mehlhorn, Ben-Asher, Dutt, & Gonzalez, 2014).…”

Section: Concepts and Definitions Of Exploration And Exploitationmentioning

confidence: 99%

Unpacking the exploration–exploitation tradeoff: A synthesis of human and animal literatures.

Mehlhorn¹,

Newell²,

Todd³

et al. 2015

Decision

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334

318

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Many decisions in the lives of animals and humans require a fine balance between the exploration of different options and the exploitation of their rewards. Do you buy the advertised car, or do you testdrive different models? Do you continue feeding from the current patch of flowers, or do you fly off to another one? Do you marry your current partner, or try your luck with someone else? The balance required in these situations is commonly referred to as the exploration-exploitation tradeoff. It features prominently in a wide range of research traditions, including learning, foraging, and decisionmaking literatures. Here, we integrate findings from these and other often-isolated literatures in order to gain a better understanding of the possible tradeoffs between exploration and exploitation, and we propose new theoretical insights that might guide future research. Specifically, we explore how potential tradeoffs depend on (1) the conceptualization of exploration and exploitation; (2) the influencing environmental, social, and individual factors; (3) the scale at which exploration and exploitation are considered; (4) the relationship and types of transitions between the two behaviors; and (5) the goals of the decision maker. We conclude that exploration and exploitation are best conceptualized as points on a continuum, and that the extent to which an agent's behavior can be interpreted as exploratory or exploitative depends upon the level of abstraction at which it is considered.

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Section: Concepts and Definitions Of Exploration And Exploitationmentioning

confidence: 99%

Unpacking the exploration–exploitation tradeoff: A synthesis of human and animal literatures.

Mehlhorn¹,

Newell²,

Todd³

et al. 2015

Decision

Self Cite

334

318

View full text Add to dashboard Cite

show abstract

“…This effect may be explained by the fact that high outcomes occur less often in the environment (low objective probability, given that the probability of the high-value outcome in the ADP is 1/3), or by the well-known phenomenon of under-exploration, by which there is a human tendency to limit their information search, even when they are given the opportunity to search extensively (Gonzalez & Dutt, 2011, 2012Hau, Pleskac, Kiefer, & Hertwig, 2008;Hills & Hertwig, 2010;Mehlhorn et al, 2014Mehlhorn et al, , 2015. We further investigate these two explanations using the IBL model ("out of the box") to make predictions in conditions where we vary the probabilities systematically and the number of samples taken before a choice is made.…”

Section: Goals and Overview Of The Current Researchmentioning

confidence: 99%

Framing From Experience: Cognitive Processes and Predictions of Risky Choice

González

Mehlhorn

2015

Cognitive Science

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A framing bias shows risk aversion in problems framed as "gains" and risk seeking in problems framed as "losses," even when these are objectively equivalent and probabilities and outcomes values are explicitly provided. We test this framing bias in situations where decision makers rely on their own experience, sampling the problem's options (safe and risky) and seeing the outcomes before making a choice. In Experiment 1, we replicate the framing bias in description-based decisions and find risk indifference in gains and losses in experience-based decisions. Predictions of an Instance-Based Learning model suggest that objective probabilities as well as the number of samples taken are factors that contribute to the lack of framing effect. We test these two factors in Experiment 2 and find no framing effect when a few samples are taken but when large samples are taken, the framing effect appears regardless of the objective probability values. Implications of behavioral results and cognitive modeling are discussed.

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“…The role of this latter belief-driven process in previous studies of the sampling paradigm is unclear. Participants are typically not informed about how options are generated, including the potential for extreme rare events (although some participants may discern this structure across multiple problems and subsequently prolong search in order to discover unexperienced rare outcomes, see Mehlhorn, Ben-Asher, Dutt, & Gonzalez, 2014).…”

Section: Choice Environmentmentioning

confidence: 99%

To act fast or to bide time? Adaptive exploration under competitive pressure

Markant¹,

Phillips²,

Kareev³

et al. 2018

Preprint

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Competitive pressure affects a wide spectrum of decisions under uncertainty. It forces the individual to balance the value of gathering more information about the quality of potential choice alternatives against the risk that competitors will act first and claim the best options. Although this tradeoff between competition and exploration has long been recognized, little is known about how people adapt their exploration of uncertain options when facing competitive pressure. We examined how competitive pressure affects exploration in the “rivals-in-the-dark” game. Two players simultaneously learn about a set of choice options and compete to claim the best one. Across three studies, we show that people adapt their exploration in response to the structure of the choice environment (including the option set size and the relative number of gains and losses) and in response to repeated competition with the same opponent. Furthermore, we present a model-based analysis showing that their behavior is best described by a compensatory strategy under which the value of further exploration is weighed against the cost of being beaten to the punch by an opponent. The results point to a process of local adaptation whereby people learn to “act fast” based on their experience in a novel competitive environment.

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Observed Variability and Values Matter: Toward a Better Understanding of Information Search and Decisions from Experience

Cited by 15 publications

References 53 publications

Unpacking the exploration–exploitation tradeoff: A synthesis of human and animal literatures.

Unpacking the exploration–exploitation tradeoff: A synthesis of human and animal literatures.

Framing From Experience: Cognitive Processes and Predictions of Risky Choice

To act fast or to bide time? Adaptive exploration under competitive pressure

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