Deeply Semantic Inductive Spatio-Temporal Learning
arXiv:1608.02693
Abstract
We present an inductive spatio-temporal learning framework rooted in inductive logic programming. With an emphasis on visuo-spatial language, logic, and cognition, the framework supports learning with relational spatio-temporal features identifiable in a range of domains involving the processing and interpretation of dynamic visuo-spatial imagery. We present a prototypical system, and an example application in the domain of computing for visual arts and computational cognitive science.
Accepted for publication at ILP 2016: 26th International Conference on Inductive Logic Programming 4th - 6th September 2016, London. Keywords: Spatio-Temporal Learning; Dynamic Visuo-Spatial Imagery; Declarative Spatial Reasoning; Inductive Logic Programming; AI and Art