3 papers
cs.AI2025
Inference of Abstraction for Grounded Predicate Logic
Hiroyuki Kido
An important open question in AI is what simple and natural principle enables a machine to reason logically for meaningful abstraction with grounded symbols. This paper explores a…
cs.AI2024
Inference of Abstraction for a Unified Account of Reasoning and Learning
Hiroyuki Kido
Inspired by Bayesian approaches to brain function in neuroscience, we give a simple theory of probabilistic inference for a unified account of reasoning and learning. We simply mod…
cs.AI2024
Inference of Abstraction for a Unified Account of Symbolic Reasoning from Data
Hiroyuki Kido
Inspired by empirical work in neuroscience for Bayesian approaches to brain function, we give a unified probabilistic account of various types of symbolic reasoning from data. We c…