How can heuristic strategies emerge from smaller building blocks? We propose Approximate Bayesian Computation (ABC) as a computational solution to this problem. As a first proof of concept, we demonstrate how a heuristic decision strategy such as …
A probabilistic causal chain A-B-C may intuitively appear to be transitive: If A probabilistically causes B, and B probabilistically causes C, A probabilistically causes C. However, probabilistic causal relations can only guaranteed to be transitive …
We investigated 4th-grade children's search strategies on sequential search tasks in which the goal is to identify an unknown target object by asking yes-no questions about its features. We used exhaustive search to identify the most efficient …
We investigate whether people rely on their causal intuitions to determine the predictive value or importance of cues. Our real-world data set consists of one criterion variable (child mortality) and nine cues (e.g., GDP per capita). We elicited …
What--if anything--can psychology and decision science contribute to risk management in financial institutions? The turmoils of recent economic crises undermine the assumptions of classical economic models and threaten to dethrone Homo oeconomicus, …
Is the mind an "intuitive statistician"? Or are humans biased and error-prone when it comes to probabilistic thinking? While researchers in the 1950s and 1960s suggested that people reason approximately in accordance with the laws of probability …
This paper investigates the role of the assumption of class-conditional independence of object features in human classification learning. This assumption holds that object feature values are statistically independent of each other, given knowledge of …
Theories of causal reasoning and learning often implicitly assume that the structural implications of causal models and empirical evidence are consistent. However, for probabilistic causal relations this may not be the case. We propose a causal …
Recently, a number of rational theories have been put forward which provide a coherent formal framework for modeling different types of causal inferences, such as prediction, diagnosis, and action planning. A hallmark of these theories is their …
In deterministic causal chains the relations "A causes B" and "B causes C" imply that "A causes C". However, this is not necessarily the case for probabilistic causal relationships: A may probabilistically cause B, and B may probabilistically cause …