The authors present a new model called RCCL (pronounced "ReCyCLe"; Represent the task, Construct a set of action strategies consistent with the task representation, Choose from among those strategies according to their success rates, and Learn new success rates for the strategies based on experience). The model explains the different ways in which people combine base-rate and case-specific cues to produce choice. It also makes additional predictions regarding variability in people's choices over time. Experiment 1 tested 58 college-age students in a problem-solving task and showed that task representations can be influenced by feedback from the environment, producing changes in base rate and cue sensitivity. Experiment 2 tested 80 college-a...
The assumption that people possess a repertoire of strategies to solve the inference problems they f...
International audienceWe used event-related potentials (ERPs) to determine the time course of mechan...
ABSTRACT—In dynamic decision-making environments, observers must continuously adjust their decision-...
The authors present a new model called RCCL (pronounced "ReCyCLe"; Represent the task, Construct a s...
In choice situations, people are usually (but not always) sensitive to the base-rates of success of ...
Decision-making in the real world presents the challenge of requiring flexible yet prompt behavior, ...
In this study, we use cognitive models to investigate how humans develop preferences for specific st...
<div><p>Many accounts of decision making and reinforcement learning posit the existence of two disti...
Probability Matching is a common and suboptimal strategy often used by participants in a Binary Pred...
Simple perceptual decision-making tasks such as the Stroop and flanker tasks are popular as a method...
What simple learning rules can allow agents to cope with changing environments? We tested whether a ...
A. S. Goodie and E. Fantino (2000) make two main criticisms of the predictions of M. C. Lovett and C...
Many decisions have to be made on the basis of knowledge about correlational structures in the envir...
The authors propose a reinforcement-learning mechanism as a model for recurrent choice and extend it...
Abstract: Cognitive flexibility is the ability to adaptively change behaviors in the face of dynamic...
The assumption that people possess a repertoire of strategies to solve the inference problems they f...
International audienceWe used event-related potentials (ERPs) to determine the time course of mechan...
ABSTRACT—In dynamic decision-making environments, observers must continuously adjust their decision-...
The authors present a new model called RCCL (pronounced "ReCyCLe"; Represent the task, Construct a s...
In choice situations, people are usually (but not always) sensitive to the base-rates of success of ...
Decision-making in the real world presents the challenge of requiring flexible yet prompt behavior, ...
In this study, we use cognitive models to investigate how humans develop preferences for specific st...
<div><p>Many accounts of decision making and reinforcement learning posit the existence of two disti...
Probability Matching is a common and suboptimal strategy often used by participants in a Binary Pred...
Simple perceptual decision-making tasks such as the Stroop and flanker tasks are popular as a method...
What simple learning rules can allow agents to cope with changing environments? We tested whether a ...
A. S. Goodie and E. Fantino (2000) make two main criticisms of the predictions of M. C. Lovett and C...
Many decisions have to be made on the basis of knowledge about correlational structures in the envir...
The authors propose a reinforcement-learning mechanism as a model for recurrent choice and extend it...
Abstract: Cognitive flexibility is the ability to adaptively change behaviors in the face of dynamic...
The assumption that people possess a repertoire of strategies to solve the inference problems they f...
International audienceWe used event-related potentials (ERPs) to determine the time course of mechan...
ABSTRACT—In dynamic decision-making environments, observers must continuously adjust their decision-...