11 citations · 15 across the 4 of their papers we have counts for
4 papers
Modularity benefits reinforcement learning agents with competing homeostatic drives
Zack Dulberg, Rachit Dubey, Isabel M. Berwian +1
The problem of balancing conflicting needs is fundamental to intelligence. Standard reinforcement learning algorithms maximize a scalar reward, which requires combining different o…
Modelling the development of counting with memory-augmented neural networks
Zack Dulberg, Taylor Webb, Jonathan Cohen
Learning to count is an important example of the broader human capacity for systematic generalization, and the development of counting is often characterized by an inflection point…
Learning Canonical Transformations
Zachary Dulberg, Jonathan Cohen
Humans understand a set of canonical geometric transformations (such as translation and rotation) that support generalization by being untethered to any specific object. We explore…
Learning Representations that Support Extrapolation
Taylor W. Webb, Zachary Dulberg, Steven M. Frankland +3
Extrapolation -- the ability to make inferences that go beyond the scope of one's experiences -- is a hallmark of human intelligence. By contrast, the generalization exhibited by c…