26 citations · 66 across the 16 of their papers we have counts for
17 papers
A Computational Model of Children's Learning and Use of Probabilities Across Different Ages
Zilong Wang, Thomas R. Shultz, Ardvan S. Nobandegani
Recent empirical work has shown that human children are adept at learning and reasoning with probabilities. Here, we model a recent experiment investigating the development of scho…
A Neural Model of Number Comparison with Surprisingly Robust Generalization
Thomas R. Shultz, Ardavan S. Nobandegani, Zilong Wang
We propose a relatively simple computational neural-network model of number comparison. Training on comparisons of the integers 1-9 enable the model to efficiently and accurately s…
Cognitive Models as Simulators: The Case of Moral Decision-Making
Ardavan S. Nobandegani, Thomas R. Shultz, Irina Rish
To achieve desirable performance, current AI systems often require huge amounts of training data. This is especially problematic in domains where collecting data is both expensive…
A Computational Model of Infant Learning and Reasoning with Probabilities
Thomas R Shultz, Ardavan S Nobandegani
Recent experiments reveal that 6- to 12-month-old infants can learn probabilities and reason with them. In this work, we present a novel computational system called Neural Probabil…
The evolution of high-fidelity social learning
Marcel Montrey, Thomas R. Shultz
A defining feature of human culture is that knowledge and technology continually improve over time. Such cumulative cultural evolution (CCE) probably depends far more heavily on ho…
Outgroup Homogeneity Bias Causes Ingroup Favoritism
Marcel Montrey, Thomas R. Shultz
Ingroup favoritism, the tendency to favor ingroup over outgroup, is often explained as a product of intergroup conflict, or correlations between group tags and behavior. Such accou…