5 papers
Hypothesis Generation and Inductive Inference in Children and Language Models
Jeffrey Qin, Wasu Top Piriyakulkij, Zhuangfei Gao +4
Real world decision-making requires constructing mental models under uncertainty over evidence, over the underlying causal rules, and over the state of the world itself. Which comp…
Prospective Compression in Human Abstraction Learning
Leonardo Hernandez Cano, Ivan Zareski, Luisa El Amouri +6
A core challenge in program synthesis is online library learning: the incremental acquisition of reusable abstractions under uncertainty about future task demands. Existing algorit…
Online library learning in human visual puzzle solving
Pinzhe Zhao, Emanuele Sansone, Marta Kryven +1
When learning a novel complex task, people often form efficient reusable abstractions that simplify future work, despite uncertainty about the future. We study this process in a vi…
PoE-World: Compositional World Modeling with Products of Programmatic Experts
Wasu Top Piriyakulkij, Yichao Liang, Hao Tang +3
Learning how the world works is central to building AI agents that can adapt to complex environments. Traditional world models based on deep learning demand vast amounts of trainin…
Cognitive maps are generative programs
Marta Kryven, Cole Wyeth, Aidan Curtis +1
Making sense of the world and acting in it relies on building simplified mental representations that abstract away aspects of reality. This principle of cognitive mapping is univer…