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https://doi.org/10.2498/cit.1001392

An Assessment of Machine Learning Methods for Robotic Discovery

Ivan Bratko

Puni tekst: engleski, pdf (274 KB) str. 247-254 preuzimanja: 424* citiraj
APA 6th Edition
Bratko, I. (2008). An Assessment of Machine Learning Methods for Robotic Discovery. Journal of computing and information technology, 16 (4), 247-254. https://doi.org/10.2498/cit.1001392
MLA 8th Edition
Bratko, Ivan. "An Assessment of Machine Learning Methods for Robotic Discovery." Journal of computing and information technology, vol. 16, br. 4, 2008, str. 247-254. https://doi.org/10.2498/cit.1001392. Citirano 05.03.2021.
Chicago 17th Edition
Bratko, Ivan. "An Assessment of Machine Learning Methods for Robotic Discovery." Journal of computing and information technology 16, br. 4 (2008): 247-254. https://doi.org/10.2498/cit.1001392
Harvard
Bratko, I. (2008). 'An Assessment of Machine Learning Methods for Robotic Discovery', Journal of computing and information technology, 16(4), str. 247-254. https://doi.org/10.2498/cit.1001392
Vancouver
Bratko I. An Assessment of Machine Learning Methods for Robotic Discovery. Journal of computing and information technology [Internet]. 2008 [pristupljeno 05.03.2021.];16(4):247-254. https://doi.org/10.2498/cit.1001392
IEEE
I. Bratko, "An Assessment of Machine Learning Methods for Robotic Discovery", Journal of computing and information technology, vol.16, br. 4, str. 247-254, 2008. [Online]. https://doi.org/10.2498/cit.1001392

Sažetak
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.

Hrčak ID: 44576

URI
https://hrcak.srce.hr/44576

Posjeta: 592 *