18 citations · 26 across the 8 of their papers we have counts for
6 papers · 1 filter
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…
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…
Neural-network simulations of memory consolidation and reconsolidation
Peter Helfer, Thomas R. Shultz
In the mammalian brain newly acquired memories depend on the hippocampus for maintenance and recall, but over time these functions are taken over by the neocortex through a process…
Bringing Order to the Cognitive Fallacy Zoo
Ardavan S. Nobandegani, William Campoli, Thomas R. Shultz
In the eyes of a rationalist like Descartes or Spinoza, human reasoning is flawless, marching toward uncovering ultimate truth. A few centuries later, however, culminating in the w…
Over-representation of Extreme Events in Decision-Making: A Rational Metacognitive Account
Ardavan S. Nobandegani, Kevin da Silva Castanheira, A. Ross Otto +1
The Availability bias, manifested in the over-representation of extreme eventualities in decision-making, is a well-known cognitive bias, and is generally taken as evidence of huma…