Humans are often faced with an exploration-versus-exploitation trade-off. A commonly used paradigm, multi-armed bandit, has shown humans to exhibit an "uncertainty bonus", which combines with estimated reward to drive exploration. However, previous studies often modeled belief updating using either a Bayesian model that assumed the reward contingency to remain stationary, or a reinforcement learning model. Separately, we previously showed that human learning in the bandit task is best captured by a dynamic-belief Bayesian model. We hypothesize that the estimated uncertainty bonus may depend on which learning model is employed. Here, we re-analyze a bandit dataset using all three learning models. We find that the dynamic-belief model capture...
How does time pressure influence exploration and decision-making? We investigated this question with...
Uncertainty plays a critical role in reinforcement learning and decision making. However, exactly ho...
Social learning is a critical adaptation for dealing with different forms of variability. Uncertaint...
Humans are often faced with an exploration-versus-exploitation trade-off. A commonly used paradigm, ...
Recently, evidence has emerged that humans approach learning using Bayesian updating rather than (mo...
In repeated decision problems for which it is possible to learn from experience, people should activ...
Humans frequently overestimate the likelihood of desirable events while underestimating the likeliho...
Humans often face sequential decision-making problems, in which information about the environmental ...
Little is known about how humans solve the exploitation/exploration trade-off. In particular, the ev...
Aim: The nature of attention, and how it interacts with learning and choice processes in the context...
Two prominent types of uncertainty that have been studied extensively are expected and unexpected un...
Computational models of learning have proved largely successful in characterising potentialmechanism...
Computational models of learning have proved largely successful in characterizing potential mechanis...
How do people decide whether to try out novel options as opposed to tried-and-testedones? We argue t...
Little is known about how humans solve the exploitation/exploration trade-off. In particular, the ev...
How does time pressure influence exploration and decision-making? We investigated this question with...
Uncertainty plays a critical role in reinforcement learning and decision making. However, exactly ho...
Social learning is a critical adaptation for dealing with different forms of variability. Uncertaint...
Humans are often faced with an exploration-versus-exploitation trade-off. A commonly used paradigm, ...
Recently, evidence has emerged that humans approach learning using Bayesian updating rather than (mo...
In repeated decision problems for which it is possible to learn from experience, people should activ...
Humans frequently overestimate the likelihood of desirable events while underestimating the likeliho...
Humans often face sequential decision-making problems, in which information about the environmental ...
Little is known about how humans solve the exploitation/exploration trade-off. In particular, the ev...
Aim: The nature of attention, and how it interacts with learning and choice processes in the context...
Two prominent types of uncertainty that have been studied extensively are expected and unexpected un...
Computational models of learning have proved largely successful in characterising potentialmechanism...
Computational models of learning have proved largely successful in characterizing potential mechanis...
How do people decide whether to try out novel options as opposed to tried-and-testedones? We argue t...
Little is known about how humans solve the exploitation/exploration trade-off. In particular, the ev...
How does time pressure influence exploration and decision-making? We investigated this question with...
Uncertainty plays a critical role in reinforcement learning and decision making. However, exactly ho...
Social learning is a critical adaptation for dealing with different forms of variability. Uncertaint...