Cognitive Modeling Challenge 2026
Jake Russin | Parallel trade-offs in human cognition and neural networks: The dynamic interplay between in-context and in-weight learning
Steven Miletiฤ | Understanding trial-by-trial variability in decision making
Tom Griffiths | The rational use of cognitive resources
Paul Masset | Multi-timescale reinforcement learning in the brain
Marcel Binz | Foundation models of human cognition
Christopher Summerfield | Comparing the learning dynamics of humans and deep networks
Marc-Lluis Vives | On the relationship between semantic representations and decision-making
Arkady Konovalov | Strategic Computations and Learning in the Social Brain
Anne Collins | Deconstructing human reinforcement learning
Toby Wise | Learning about uncertainty: mechanisms and implications for mental health
Michael J. Frank | Clustering and generalization of abstract structures in reinforcement learning
Robert C. Wilson | Information, randomization, and simulation in exploration and exploitation
Weiji Ma | The cognitive science of complex planning
Charley Wu | Visual-spatial dynamics drive adaptive social learning in immersive environments
Taicheng Huang | Beyond the hippocampus as a predictive map
Seongmin A. Park | Structural abstraction and behavioral flexibility
Matt Nassar | Dynamic representations for behavioral flexibility
Mark Ho | Construction of mental representations in human planning
Haoxue Fan | Trait somatic anxiety is associated with reduced directed exploration and underestimation of uncertainty
Stefano Palminteri | Reinforcement learning biases that makes us smart
Zhaoyu Zuo | Working memory guides action valuation in model-based inference
Shen Xu | Crash tutorials on fitting hierarchical Bayesian reinforcement learning models
Huadong Xiong | Neural network modeling reveals diverse human exploration behaviors via state space analysis