A Reinforcement Learning Based Algorithm for Robot Action Planning-Reference-Cited by-同舟云学术

A Reinforcement Learning Based Algorithm for Robot Action Planning

Published:2018-09-29 Issue: Volume: Page:493-503
ISSN:2211-0984
Container-title:Advances in Service and Industrial Robotics
language:
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Author:

Švaco Marko,Jerbić Bojan,Polančec Mateo,Šuligoj Filip

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-00232-9_52

Reference21 articles.

1. Švaco, M., Jerbić, B., Šekoranja, B.: Task planning based on the interpretation of spatial structures. Tehnicki vjesnik - Technical Gazette 24(2) (2017)

2. Švaco, M., Jerbić, B., Šuligoj, F.: ARTgrid: a two-level learning architecture based on adaptive resonance theory. Adv. Artif. Neural Syst. 2014, 1–9 (2014)

3. Ekvall, S., Kragic, D.: Robot learning from demonstration: a task-level planning approach. Int. J. Adv. Rob. Syst. 5(3), (2008)

4. Asada, M., Noda, S., Tawaratsumida, S., Hosoda, K.: Vision-based reinforcement learning for purposive behavior acquisition. In: IEEE International Conference on Robotics and Automation, Proceedings., vol. 1, pp. 146–153

5. Yiannis, D., Hayes, G.: Imitative Learning Mechanisms in Robots and Humans (1996)

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