A tutorial on Gaussian process regression: Modelling, exploring, and exploiting functions
This tutorial introduces the reader to Gaussian process regression as an expressive tool to
model, actively explore and exploit unknown functions. Gaussian process regression is a …
model, actively explore and exploit unknown functions. Gaussian process regression is a …
Intrinsic motivation, curiosity, and learning: Theory and applications in educational technologies
This chapter studies the bidirectional causal interactions between curiosity and learning and
discusses how understanding these interactions can be leveraged in educational …
discusses how understanding these interactions can be leveraged in educational …
Active inference, curiosity and insight
This article offers a formal account of curiosity and insight in terms of active (Bayesian)
inference. It deals with the dual problem of inferring states of the world and learning its …
inference. It deals with the dual problem of inferring states of the world and learning its …
[HTML][HTML] Federated inference and belief sharing
This paper concerns the distributed intelligence or federated inference that emerges under
belief-sharing among agents who share a common world—and world model. Imagine, for …
belief-sharing among agents who share a common world—and world model. Imagine, for …
Asking the right questions about the psychology of human inquiry: Nine open challenges
The ability to act on the world with the goal of gaining information is core to human
adaptability and intelligence. Perhaps the most successful and influential account of such …
adaptability and intelligence. Perhaps the most successful and influential account of such …
Generalized information theory meets human cognition: Introducing a unified framework to model uncertainty and information search
Searching for information is critical in many situations. In medicine, for instance, careful
choice of a diagnostic test can help narrow down the range of plausible diseases that the …
choice of a diagnostic test can help narrow down the range of plausible diseases that the …
Conservative forgetful scholars: How people learn causal structure through sequences of interventions.
Interacting with a system is key to uncovering its causal structure. A computational
framework for interventional causal learning has been developed over the last decade, but …
framework for interventional causal learning has been developed over the last decade, but …
It's new, but is it good? How generalization and uncertainty guide the exploration of novel options.
How do people decide whether to try out novel options as opposed to tried-and-tested
ones? We argue that they infer a novel option's reward from contextual information learned …
ones? We argue that they infer a novel option's reward from contextual information learned …
The ventral striatum dissociates information expectation, reward anticipation, and reward receipt
Do dopaminergic reward structures represent the expected utility of information similarly to a
reward? Optimal experimental design models from Bayesian decision theory and statistics …
reward? Optimal experimental design models from Bayesian decision theory and statistics …
[HTML][HTML] Children's sequential information search is sensitive to environmental probabilities
JD Nelson, B Divjak, G Gudmundsdottir, LF Martignon… - Cognition, 2014 - Elsevier
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 …
the goal is to identify an unknown target object by asking yes–no questions about its …