From machine learning to robotics: Challenges and opportunities for embodied intelligence
Machine learning has long since become a keystone technology, accelerating science and
applications in a broad range of domains. Consequently, the notion of applying learning …
applications in a broad range of domains. Consequently, the notion of applying learning …
Inductive logic programming at 30: a new introduction
A Cropper, S Dumančić - Journal of Artificial Intelligence Research, 2022 - jair.org
Inductive logic programming (ILP) is a form of machine learning. The goal of ILP is to induce
a hypothesis (a set of logical rules) that generalises training examples. As ILP turns 30, we …
a hypothesis (a set of logical rules) that generalises training examples. As ILP turns 30, we …
Inductive logic programming at 30
Inductive logic programming (ILP) is a form of logic-based machine learning. The goal is to
induce a hypothesis (a logic program) that generalises given training examples and …
induce a hypothesis (a logic program) that generalises given training examples and …
[PDF][PDF] Inductive logic programming at 30: a new introduction
A Cropper, S Dumancic - Journal of Artificial Intelligence …, 1993 - researchgate.net
Inductive logic programming (ILP) is a form of machine learning. The goal of ILP is to induce
a hypothesis (a set of logical rules) that generalises given training examples. In contrast to …
a hypothesis (a set of logical rules) that generalises given training examples. In contrast to …
Reasoning on the whole structure of buildings using a logical relational learning framework
M LAUNI - 2014 - politesi.polimi.it
Semantic mapping for autonomous mobile robots includes the place classification task that
associates semantic labels (like 'corridor'or 'office') to rooms perceived in an environment …
associates semantic labels (like 'corridor'or 'office') to rooms perceived in an environment …