We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.
To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure no-reply@cambridge.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
Edited by
Irene Cogliati Dezza, University College London,Eric Schulz, Max-Planck-Institut für biologische Kybernetik, Tübingen,Charley M. Wu, Eberhard-Karls-Universität Tübingen, Germany
Searching for information in a goal-directed manner is central for learning, diagnosis, and prediction. Children ask questions to learn new concepts, doctors conduct medical tests to diagnose their patients, and scientists perform experiments to test their theories. But what makes a good query? What principles govern human information acquisition and how do people decide which query to conduct to achieve their goals? What challenges need to be met to advance the theory and psychology of human inquiry? Addressing these issues, we introduce the conceptual and mathematical ideas underlying different models of the value of information, what purpose these models serve in psychological research, and how they can be integrated in a unified computational framework. We also discuss the conflict between short- and long-term efficiency of prominent methods for query selection, and the resulting normative and methodological implications for studying human sequential search. A final point of discussion concerns the relations between probabilistic (Bayesian) models of the value of information and heuristic search strategies, and the insights that can be gained from bridging different levels of analysis and types of models. We conclude by discussing open questions and challenges that research needs to address to build a comprehensive theory of human information acquisition.
Recommend this
Email your librarian or administrator to recommend adding this to your organisation's collection.