Original scientific paper
https://doi.org/10.2498/cit.1001392
An Assessment of Machine Learning Methods for Robotic Discovery
Ivan Bratko
Abstract
In this paper we consider autonomous robot discovery through experimentation in the robot’s environment. We analyse the applicability of machine learning (ML) methods with respect to various levels of robot discovery tasks, from extracting simple laws among the observed variables, to discovering completely new notions that were never mentioned in the data directly. We first present some illustrative experiments in robot learning in the XPERO European project. Then we formulate a systematic list of types of learning or discovery tasks, and discuss the suitability of chosen ML methods for these tasks.
Keywords
Hrčak ID:
44576
URI
Publication date:
30.12.2008.
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