98 citations · 123 across the 10 of their papers we have counts for
11 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…
Modeling human intention inference in continuous 3D domains by inverse planning and body kinematics
Yingdong Qian, Marta Kryven, Tao Gao +2
How to build AI that understands human intentions, and uses this knowledge to collaborate with people? We describe a computational framework for evaluating models of goal inference…
Map Induction: Compositional spatial submap learning for efficient exploration in novel environments
Sugandha Sharma, Aidan Curtis, Marta Kryven +2
Humans are expert explorers. Understanding the computational cognitive mechanisms that support this efficiency can advance the study of the human mind and enable more efficient exp…
Communicating Natural Programs to Humans and Machines
Samuel Acquaviva, Yewen Pu, Marta Kryven +6
The Abstraction and Reasoning Corpus (ARC) is a set of procedural tasks that tests an agent's ability to flexibly solve novel problems. While most ARC tasks are easy for humans, th…
Vector-based Pedestrian Navigation in Cities
Christian Bongiorno, Yulun Zhou, Marta Kryven +5
How do pedestrians choose their paths within city street networks? Researchers have tried to shed light on this matter through strictly controlled experiments, but an ultimate answ…
Learning abstract structure for drawing by efficient motor program induction
Lucas Y. Tian, Kevin Ellis, Marta Kryven +1
Humans flexibly solve new problems that differ qualitatively from those they were trained on. This ability to generalize is supported by learned concepts that capture structure com…
Program Synthesis with Pragmatic Communication
Yewen Pu, Kevin Ellis, Marta Kryven +2
Program synthesis techniques construct or infer programs from user-provided specifications, such as input-output examples. Yet most specifications, especially those given by end-us…