The present paper motivates the study of mind change complexity for learning minimal models of length-bounded logic programs. It establishes ordinal mind change complexity bounds ...
A number of today's state-of-the-art planners are based on forward state-space search. The impressive performance can be attributed to progress in computing domain independen...
Reinforcement Learning (RL) is the study of programs that improve their performance by receiving rewards and punishments from the environment. Most RL methods optimize the discoun...
Background: When investigating covariate interactions and group associations with standard regression analyses, the relationship between the response variable and exposure may be ...
John J. Heine, Walker H. Land Jr., Kathleen M. Ega...
We present an efficient method for learning part-based object class models from unsegmented images represented as sets of salient features. A model includes parts' appearance...