ReviewEntropy (Basel, Switzerland)2021
Information Theory for Agents in Artificial Intelligence, Psychology, and Economics.
Review in Entropy (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed, 0 citations in OpenAlex.
- Decision, Inference, and Information: Formal Equivalences Under Active Inference.Entropy (Basel, Switzerland) · 2025Review
- Object spatial certainty as a measure of spatial variability and its influence on attention.Scientific reports · 2025Article
- On the potential of transfer entropy in turbulent dynamical systems.Scientific reports · 2023Article
- Information Theory Opens New Dimensions in Experimental Studies of Animal Behaviour and Communication.Animals : an open access journal from MDPI · 2023Review
- Entropy, Economics, and Criticality.Entropy (Basel, Switzerland) · 2022Article
- Entropy, Information, and the Updating of Probabilities.Entropy (Basel, Switzerland) · 2021Article
- A Maximum Entropy Model of Bounded Rational Decision-Making with Prior Beliefs and Market Feedback.Entropy (Basel, Switzerland) · 2021Article
- Interactive Design Psychology and Artificial Intelligence-Based Innovative Exploration of Anglo-American Traumatic Narrative Literature.Frontiers in psychology · 2021Article
- The Influence of "Artificial Intelligence + Human-Computer Interaction" on Teachers' Psychological Changes in Academic Management in Colleges.Frontiers in psychology · 2021Article
Corrections and comments
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Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This review looks at some of the central relationships between artificial intelligence, psychology, and economics through the lens of information theory, specifically focusing on formal models of decision-theory. In doing so we look at a particular approach that each field has adopted and how information theory has informed the development of the ideas of each field. A key theme is expected utility theory, its connection to information theory, the Bayesian approach to decision-making and forms of (bounded) rationality. What emerges from this review is a broadly unified formal perspective derived from three very different starting points that reflect the unique principles of each field. Each of the three approaches reviewed can, in principle at least, be implemented in a computational model in such a way that, with sufficient computational power, they could be compared with human abilities in complex tasks. However, a central critique that can be applied to all three approaches was first put forward by Savage in
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.