Computational Cognitive Modeling
Overview
The field builds computational accounts of mental processes, from memory and language to decision-making, emotion, and social reasoning. Researchers use Bayesian and reinforcement-learning models, resource-rational algorithms, cognitive architectures, neural networks, and program induction, testing them against behavioral, neural, and real-world data. Newer work also uses language models and automated experiments to generate and compare theories. A central challenge is distinguishing genuine explanatory mechanisms from systems that merely match behavior, while ensuring models generalize beyond the tasks and data on which they were developed.
Latest papers
126 papers7 papers in the last four weeks, down 56% on the four weeks before. 0.0% of all new papers.