NDLI: Towards iterative learning of autonomous robots using ILP

Content Provider	IEEE Xplore Digital Library
Author	Akhtar, N. Fuller, M. Kahl, B. Henne, T.
Copyright Year	2011
Description	Author affiliation: Department of Computer Science of Bonn-Rhein-Sieg University of Applied Sciences, Grantham-Allee 20, 53757 Sankt Augustin, Germany (Akhtar, N.; Fuller, M.) \|\| Bonn-Rhein-Sieg University of Applied Sciences (Kahl, B.; Henne, T.)
Abstract	Inductive Logic Programming (ILP) induces first-order clausal theories from learning examples (positive and negative) and knowledge of the domain. Such theories can be used for gradually increasing the understanding of a robot about its world through iterative learning process. In this work we present a method for autonomous creation of negative examples for an ILP learner (i.e. sifting method). We also present a method for managing the iterative learning process (i.e. step transition method) for an autonomous robot that uses the ILP learner for learning. The sifting method uses ‘out-of-domain’ values of the parameters involved in the learning process to create a set of possible negative examples. From these examples the robot autonomously selects those which allow it to efficiently learn better hypotheses. The step transition method enables the autonomous robot to decide how should it learn the new knowledge such that it can also gain profit from its experience. The robot makes this decision by comparing results of two different learning processes conducted on different data sets produced by the same action of the robot. The proposed methods are developed using the ILP learner Aleph, however they can also be used with other similar ILP learners. We experiment with these methods for learning primitive concepts for a mobile autonomous robot in a simple world. Results of the experiments show that the robot learns meaningful definitions of different physical notions in a hierarchical manner.
Starting Page	409
Ending Page	414
File Size	178369
Page Count	6
File Format	PDF
ISBN	9781457711589
e-ISBN	9781457711596
DOI	10.1109/ICAR.2011.6088625
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-06-20
Publisher Place	Estonia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robot sensing systems Space exploration Time measurement Educational institutions Noise Learning systems
Content Type	Text
Resource Type	Article

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