Local search and the evolution of world models

NR Bramley, B Zhao, T Quillien… - Topics in Cognitive …, 2023 - Wiley Online Library
An open question regarding how people develop their models of the world is how new
candidates are generated for consideration out of infinitely many possibilities. We discuss …

Learning to Infer Generative Template Programs for Visual Concepts

RK Jones, S Chaudhuri, D Ritchie - arXiv preprint arXiv:2403.15476, 2024 - arxiv.org
People grasp flexible visual concepts from a few examples. We explore a neurosymbolic
system that learns how to infer programs that capture visual concepts in a domain-general …

How to Think About Benchmarking Neurosymbolic AI?

J Ott, A Ledaguenel, C Hudelot… - … International Workshop on …, 2023 - hal.science
Neurosymbolic artificial intelligence is a growing field of research aiming at combining
neural networks with symbolic systems, including their respective learning and reasoning …

Abstracted Gaussian Prototypes for One-Shot Concept Learning

C Zou, KJ Kurtz - arXiv preprint arXiv:2408.17251, 2024 - arxiv.org
We introduce a cluster-based generative image segmentation framework to encode higher-
level representations of visual concepts based on one-shot learning inspired by the …

Understanding Boolean Function Learnability on Deep Neural Networks: PAC Learning Meets Neurosymbolic Models

M Nicolau, AR Tavares, Z Zhang, P Avelar… - arXiv preprint arXiv …, 2020 - arxiv.org
Computational learning theory states that many classes of boolean formulas are learnable in
polynomial time. This paper addresses the understudied subject of how, in practice, such …