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 explicitly mentioned in the data directly. We first present some illustrative experiments in robot learning in the XPERO European project. Then we formulate criteria for a comparison of learning methods and a systematic list of types of learning or discovery tasks, and discuss the suitability of chosen ML methods for these tasks.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Awaad, I., Leon, B.: XPERSim: Simulation of the robotic experimenter. XPERO Report on R&D 1 (September 2006)
Bratko, I.: Prolog Programming for Artificial Intelligence, 3rd edn. Addison-Wesley / Pearson, Reading (2001)
Bratko, I., Šuc, D.: Learning qualitative models. AI Magazine 24(4), 107–119 (2003)
Bratko, I., Šuc, D., Awaad, I., Demšar, J., Gemeiner, P., Guid, M., Leon, B., Mestnik, M., Prankl, J., Prassler, E., Vincze, M., Žabkar, J.: Initial experiments in robot discovery in XPERO. In: ICRA 2007 workshop Concept Learning for Embodied Agents, Rome (April 2007)
Clark, P., Niblett, T.: The CN2 induction algorithm. Machine Learning 3, 262–284 (1989)
Demšar, J., Zupan, B.: Orange: Data Mining Fruitful & Fun - From Experimental Machine Learning to Interactive Data Mining (2006), http://www.ailab.si/orange
Džeroski, S., Todorovski, L.: Discovering dynamics. In: Proceedings of the 10th International Conference on Machine Learning, pp. 97–103. Morgan Kaufmann, San Francisco (1993)
Križman, V., Džeroski, S., Kompare, B.: Discovering dynamics from measured data. Electrotechnical Review 62, 191–198 (1995)
Križman, V.: Automatic Discovery of the Structure of Dynamic System Models. PhD thesis, Faculty of Computer and Information Sciences, University of Ljubljana (1998)
Kuipers, B.: Qualitative Reasoning: Modeling and Simulation with Incomplete Knowledge. MIT Press, Cambridge (1994)
Leban, G., Žabkar, J., Bratko, I.: An experiment in robot discovery with ILP. In: Železný, F., Lavrač, N. (eds.) ILP 2008. LNCS (LNAI), vol. 5194, pp. 77–90. Springer, Heidelberg (2008)
Muggleton, S.: Inverse entailment and Progol. New Generation Computing 13, 245–286 (1995)
Srinivasan, A.: The Aleph Manual. Technical Report, Computing Laboratory, Oxford University (2000), http://web.comlab.ox.ac.uk/oucl/research/areas/machlearn/Aleph/
Šuc, D.: Machine Reconstruction of Human Control Strategies, Ph.D. Thesis, Faculty of Computer and Information Sc., University of Ljubljana (2001)
Šuc, D.: Machine Reconstruction of Human Control Strategies. Frontiers Artificial Intelligence Appl., vol. 99. IOS Press, Amsterdam (2003)
Šuc, D., Vladušič, D., Bratko, I.: Qualitatively Faithful Quantitative Prediction. Artificial Intelligence 158(2), 190–219 (2004)
Žabkar, J., Bratko, I., Demšar, J.: Learning qualitative models through partial derivatives by Padé. In: Proc. QR 2007, 21st International Workshop on Qualitative Reasoning, Aberystwyth, Wales, UK, pp. 193–202 (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Bratko, I. (2010). Comparison of Machine Learning for Autonomous Robot Discovery. In: Koronacki, J., Raś, Z.W., Wierzchoń, S.T., Kacprzyk, J. (eds) Advances in Machine Learning I. Studies in Computational Intelligence, vol 262. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05177-7_22
Download citation
DOI: https://doi.org/10.1007/978-3-642-05177-7_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-05176-0
Online ISBN: 978-3-642-05177-7
eBook Packages: EngineeringEngineering (R0)