DagRep.1.3.67.pdf
- Filesize: 1.02 MB
- 29 pages
Document
Exploration and Curiosity in Robot Learning and Inference (Dagstuhl Seminar 11131)
Authors and all authors of the abstracts in this report
-
Part of:
Issue:
Dagstuhl Reports, Volume 1, Issue 3
Volume: Dagstuhl Reports, Volume 1
Journal: Dagstuhl Reports (DagRep) - License:
Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported license
- Publication Date: 2011-07-28
Cite As Get BibTex
Jeremy L. Wyatt, Peter Dayan, Ales Leonardis, and Jan Peters. Exploration and Curiosity in Robot Learning and Inference (Dagstuhl Seminar 11131). In Dagstuhl Reports, Volume 1, Issue 3, pp. 67-95, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2011)
https://doi.org/10.4230/DagRep.1.3.67
Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 11131 ``Exploration and Curiosity in Robot Learning and Inference''. This seminar was concerned with answering the question: how should a robot choose its actions and experiences so as to maximise the effectiveness of its learning?}. The seminar brought together workers from three fields: machine learning, robotics and computational neuroscience. The seminar gave an overview of active research, and identified open research problems. In particular the seminar identified the difficulties in moving from theoretically well grounded notions of curiosity to practical robot implementations.
Subject Classification
Keywords
- Artificial Intelligence
- Robotics
- Learning
- Exploration
- Curiosity
Metrics
- Access Statistics
-
Total Accesses (updated on a weekly basis)
0PDF Downloads