We present a model of intuitive inference, called “local thinking, ” in which an agent combines data received from the external world with information retrieved from memory to evaluate a hypothesis. In this model, selected and limited recall of information follows a version of the respresentativeness heuristic. The model can account for some of the evidence on judgment biases, including conjunction and disjunction fallacies, but also for several anomalies related to demand for insurance. Key words: local thinking, representativeness, stereotypes, insuranc
As a matter of fact, humans continuously delegate and distribute cognitive functions to the environm...
A model of artificial perception based on self-organizing data into hierarchical structures is gener...
We investigate whether people rely on their causal intuitions to determine the predictive value or i...
We present a model of judgment under uncertainty, in which an agent combines data received from the ...
In many economic decisions, people estimate probabilities, such as the likelihood that a risk materi...
We explore the idea that judgment by representativeness reflects the workings of memory. In our mode...
Diagnostic hypothesis-generation processes are ubiquitous in human reasoning. For example, clinician...
We explore the idea that judgment by representativeness reflects the workings of memory. In our mode...
Student difficulty in the study of probability arises in intuitively-based misconceptions derived fr...
Experts are increasingly being called upon to build decision support systems. Expert intuitions and ...
The present work describes the model of heuristic judgment of Kahneman & Frederick (2002) and two ex...
Sensemaking is the active process of constructing a meaningful representation (i.e., making sense) o...
The fast-and-frugal heuristics approach to probabilistic inference assumes that individuals often em...
Copyright © 2013 Christian Lebiere et al. This is an open access article distributed under the Creat...
Based on the assessment that humans do not think as a bayesian would, we suggest a model of bounded ...
As a matter of fact, humans continuously delegate and distribute cognitive functions to the environm...
A model of artificial perception based on self-organizing data into hierarchical structures is gener...
We investigate whether people rely on their causal intuitions to determine the predictive value or i...
We present a model of judgment under uncertainty, in which an agent combines data received from the ...
In many economic decisions, people estimate probabilities, such as the likelihood that a risk materi...
We explore the idea that judgment by representativeness reflects the workings of memory. In our mode...
Diagnostic hypothesis-generation processes are ubiquitous in human reasoning. For example, clinician...
We explore the idea that judgment by representativeness reflects the workings of memory. In our mode...
Student difficulty in the study of probability arises in intuitively-based misconceptions derived fr...
Experts are increasingly being called upon to build decision support systems. Expert intuitions and ...
The present work describes the model of heuristic judgment of Kahneman & Frederick (2002) and two ex...
Sensemaking is the active process of constructing a meaningful representation (i.e., making sense) o...
The fast-and-frugal heuristics approach to probabilistic inference assumes that individuals often em...
Copyright © 2013 Christian Lebiere et al. This is an open access article distributed under the Creat...
Based on the assessment that humans do not think as a bayesian would, we suggest a model of bounded ...
As a matter of fact, humans continuously delegate and distribute cognitive functions to the environm...
A model of artificial perception based on self-organizing data into hierarchical structures is gener...
We investigate whether people rely on their causal intuitions to determine the predictive value or i...