
...implement algorithms to revise and learn firstorder logical theories, written in clausal form (as...trees and gradient descent for learning, and are founded on basic...

...the exploration of techniques for learning and refining first order theories, as the necessary step for applying machine learning methodologies to real world applications...that enables the system to learn a structured knowledge base is proposed. moreover, the learning system described in the paper can be used both to learn new knowledge from scratch and...

...humans to
more efficiently teach firstorder concepts to computers. prior work has shown that first order horn theories can be learned
using a polynomial number of...teachers. these results show, in theory,
the potential for incorporating objectbased queries into firstorder learning algorithms in order to reduce human teaching
effort...


...new algorithm called siao1 for learning first order logic rules with genetic algo...high level rep resentation for learning rules in first order logic and may deal with...

...the representation and learning of a firstorder theory using neural networks is still an open problem. we define a propositional
theory refinement system which uses min...and extend it to the firstorder case. in this
extension, the...

...inductive learning of firstorder theory based on examples has serious...search space needed, making existing learning approaches perform poorly when compared to the propositional approach. moreover, in order to choose the appropiate candidates...

...the problem of learning universally quantified function free first order horn expressions from equivalence and...afp92] for several models of learning in first order logic. it is shown that exact learning is possible with membership and...

...the application of in cremental firstorder logic learning techniques in the docu ment...

...proposes the application of incremental firstorder logic learning techniques in the document layout...