Inductive logic programming (ilp) and reasoning by analogy in context of embodied robot learning
Journal
International Journal of Agent Technologies and Systems (IJATS)
Date Issued
2010-04-01
Author(s)
Poprcova, Vesna
Stojanov, Georgi
Abstract
The ability of reasoning by analogy seems to be essential for many
cognitive processes from low and high level perception to categorization. Intuitively,
the idea is to use old knowledge in order to explain new observations similar in some
ways to what is already known. In some sense it is opposite of induction where in order
to explain the observations one comes up with new hypotheses/theories. Therefore, a
system capable of both ways of reasoning would be superior to either. In this paper we
first present an overview of Inductive Logic Programming (ILP) systems that use
reasoning by analogy. Then we present the results of applying Analogical Prediction to
problem that arise in the context of physically embodied robot which tries to learn
regularities in its environment.
cognitive processes from low and high level perception to categorization. Intuitively,
the idea is to use old knowledge in order to explain new observations similar in some
ways to what is already known. In some sense it is opposite of induction where in order
to explain the observations one comes up with new hypotheses/theories. Therefore, a
system capable of both ways of reasoning would be superior to either. In this paper we
first present an overview of Inductive Logic Programming (ILP) systems that use
reasoning by analogy. Then we present the results of applying Analogical Prediction to
problem that arise in the context of physically embodied robot which tries to learn
regularities in its environment.
Subjects
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