How do inference rules for causal learning themselves change developmentally? A model of the development of causal reasoning must address this question, as well as specify the …
A Holzinger - Joint European conference on machine learning and …, 2021 - Springer
Enormous advances in the domain of statistical machine learning, the availability of large amounts of training data, and increasing computing power have made Artificial Intelligence …
Developmental psychologists coined the term" theory of mind" to describe how we understand our shifting mental states in daily life. Over the past twenty years researchers …
An exploration of how computer algorithms can be applied to our everyday lives to solve common decision-making problems and illuminate the workings of the human mind. What …
Inducing causal relationships from observations is a classic problem in scientific inference, statistics, and machine learning. It is also a central part of human learning, and a task that …
Children's causal learning has been characterized as a rational process, in which children appropriately evaluate evidence from their observations and actions in light of their existing …
The past few decades have seen an explosion of research on causal reasoning in philosophy, computer science, and statistics, as well as descriptive work in psychology. In …
Compact representations of the environment allow humans to behave efficiently in a complex world. Reinforcement learning models capture many behavioral and neural effects …
People can behave in a way that is consistent with Bayesian models of cognition, despite the fact that performing exact Bayesian inference is computationally challenging. What …