Decision
Introduction
Decision, 11(4)
INTEREST CATEGORY: CONSUMER BEHAVIOR
POSTING TYPE: TOCs
The interface between machine learning, artificial intelligence, and decision research
—Davis-Stober, Clintin P.; Erev, Ido; Bhatia, Sudeep []
Attention-driven imitation in consumer reviews
—Alba, Charles; Walasek, Lukasz; Spektor, Mikhail S. []
Recommender systems: Friend (of choice) or foe? A large-scale field experiment in online shopping platforms
—Nobel, Nurit []
From DDMs to DNNs: Using process data and models of decision making to improve human-AI interactions
—Gopnarayan, Mrugsen Nagsen; Aru, Jaan; Gluth, Sebastian []
Doing artificial intelligence (AI): Algorithmic decision support as a human activity
—Meyer, Joachim []
Boosting human competences with interpretable and explainable artificial intelligence
—Herzog, Stefan M.; Franklin, Matija []
Dimensions of disagreement: Divergence and misalignment in cognitive science and artificial intelligence
—Oktar, Kerem; Sucholutsky, Ilia; Lombrozo, Tania; Griffiths, Thomas L. []
Possibilities for decision science in the metaverse
—Dhami, Mandeep K.; Zhu, Ying []
Cognitive graphs: Representational substrates for planning
—Yoo, Jungsun; Chrastil, Elizabeth R.; Bornstein, Aaron M. []
Why context should matter
—Bhui, Rahul; Dubey, Rachit []
Verbal reports as data revisited: Using natural language models to validate cognitive models
—Ostrovsky, Tehilla; Newell, Ben R. []
Using artificial intelligence to fit, compare, evaluate, and discover computational models of decision behavior
—Kvam, Peter D.; Sokratous, Konstantina; Fitch, Anderson; Hintze, Arend []
Machine learning for modeling human decisions
—Reichman, Daniel; Peterson, Joshua C.; Griffiths, Thomas L. []
Using machine learning to evaluate and enhance models of probabilistic inference
—Gl繹ckner, Andreas; Jekel, Marc; Lisovoj, Daria []
Using machine learning to create an adaptable, scalable, and interpretable behavioral model
—Shoshan, Vered; Hazan, Tamir; Plonsky, Ori []
Combining the aggregated forecasts: An efficient method for improving accuracy by stacking multiple weighting models
—Huang, Shu; Golman, Russell; Broomell, Stephen B. []
Decisions as ill-posed problems: A scoping review of regularization methods in decision science
—Hoffmann, Janina A. []
A psychologically informed approach to actuarial decision making
—Simchon, Almog; Gilead, Michael []