Add to ORKGHumans often seek information to minimize the pervasive effect of uncertainty on decisions. Current theories explain how much knowledge people should gather before a decision, based on the cost-benefit structure of the problem at hand. Here, we demonstrate that this framework omits a crucial agent-related factor: the cognitive effort expended while collecting information. Using an active sampling model, we unveil a speed-efficiency trade-off whereby more informative samples take longer to find. Crucially, under sufficient time pressure, humans can break this trade-off, sampling both faster and more efficiently. Computational modelling demonstrates the existence of a cost of cognitive effort which, when incorporated into theoretical models, ...
In many learning or inference tasks human behavior approximates that of a Bayesian ideal observer, s...
Humans navigate daily decision-making by flexibly choosing appropriate approximations of what ought ...
We show how information acquisition costs can be identified using observable choice data. Identifyin...
In statistics and machine learning, model accuracy is traded off with complexity, which can be viewe...
Human decisions are based on finite information, which makes them inherently imprecise. But what det...
In many environments it is costly for decision makers to determine which option is best for them bec...
Collecting (or “sampling”) information that one expects to be useful is a powerful way to facil-itat...
How do people ask questions to zero in on a correct answer? Although we can formally define an optim...
This paper studies the choice of an individual who acquires information before choosing an action fr...
It is often unclear which course of action gives the best outcome. We can reduce this uncertainty by...
The Effort-Accuracy framework (E-Af) of decision making predicts that as the computational demands o...
One key question is whether people rely on frugal heuristics or full-information strategies when mak...
The focus of this paper is the development of a computational model for intelligent agents that deci...
Information sampling is often biased towards seeking evidence that confirms one's prior beliefs. Des...
Successful behaviour depends on the right balance between maximising reward and soliciting informati...
In many learning or inference tasks human behavior approximates that of a Bayesian ideal observer, s...
Humans navigate daily decision-making by flexibly choosing appropriate approximations of what ought ...
We show how information acquisition costs can be identified using observable choice data. Identifyin...
In statistics and machine learning, model accuracy is traded off with complexity, which can be viewe...
Human decisions are based on finite information, which makes them inherently imprecise. But what det...
In many environments it is costly for decision makers to determine which option is best for them bec...
Collecting (or “sampling”) information that one expects to be useful is a powerful way to facil-itat...
How do people ask questions to zero in on a correct answer? Although we can formally define an optim...
This paper studies the choice of an individual who acquires information before choosing an action fr...
It is often unclear which course of action gives the best outcome. We can reduce this uncertainty by...
The Effort-Accuracy framework (E-Af) of decision making predicts that as the computational demands o...
One key question is whether people rely on frugal heuristics or full-information strategies when mak...
The focus of this paper is the development of a computational model for intelligent agents that deci...
Information sampling is often biased towards seeking evidence that confirms one's prior beliefs. Des...
Successful behaviour depends on the right balance between maximising reward and soliciting informati...
In many learning or inference tasks human behavior approximates that of a Bayesian ideal observer, s...
Humans navigate daily decision-making by flexibly choosing appropriate approximations of what ought ...
We show how information acquisition costs can be identified using observable choice data. Identifyin...