7 citations · 12 across the 8 of their papers we have counts for
5 papers · 1 filter
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…
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…
Converting Cascade-Correlation Neural Nets into Probabilistic Generative Models
Ardavan Salehi Nobandegani, Thomas R. Shultz
Humans are not only adept in recognizing what class an input instance belongs to (i.e., classification task), but perhaps more remarkably, they can imagine (i.e., generate) plausib…