Abstract
This paper focuses on developing a team of mobile robots capable of learning via human interaction. A modified Q-learning algorithm incorporating a teacher is proposed. The paper first concentrates on simplifying the Q-learning algorithm to be implemented on small and simple team of robots having limited capabilities of memory and computational power. Second it concentrates on the incorporation of a human teacher in the Q-learning algorithm. Experiments using the well-known robot simulator Webots on both single and multi-target tracking tasks have been conducted. The achieved results show the success of the proposed algorithm in the over all system performance.
| Original language | English |
|---|---|
| Title of host publication | 2008 International Conference on Computer Engineering and Systems, ICCES 2008 |
| Pages | 173-178 |
| Number of pages | 6 |
| DOIs | |
| Publication status | Published - 2008 |
| Event | 2008 International Conference on Computer Engineering and Systems, ICCES 2008 - Cairo, Egypt Duration: Nov 25 2008 → Nov 27 2008 |
Other
| Other | 2008 International Conference on Computer Engineering and Systems, ICCES 2008 |
|---|---|
| Country | Egypt |
| City | Cairo |
| Period | 11/25/08 → 11/27/08 |
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Keywords
- Human-robot interaction
- Machine learning
- Q-learning
- Reinforcement learning
ASJC Scopus subject areas
- Computer Science Applications
- Hardware and Architecture
- Software
Cite this
Multi target tracking using a compact Q-learning with a teacher. / Saad, E. M.; Awadalla, M. H.; Hamdy, A. M.; Ali, H. I.
2008 International Conference on Computer Engineering and Systems, ICCES 2008. 2008. p. 173-178 4772991.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Multi target tracking using a compact Q-learning with a teacher
AU - Saad, E. M.
AU - Awadalla, M. H.
AU - Hamdy, A. M.
AU - Ali, H. I.
PY - 2008
Y1 - 2008
N2 - This paper focuses on developing a team of mobile robots capable of learning via human interaction. A modified Q-learning algorithm incorporating a teacher is proposed. The paper first concentrates on simplifying the Q-learning algorithm to be implemented on small and simple team of robots having limited capabilities of memory and computational power. Second it concentrates on the incorporation of a human teacher in the Q-learning algorithm. Experiments using the well-known robot simulator Webots on both single and multi-target tracking tasks have been conducted. The achieved results show the success of the proposed algorithm in the over all system performance.
AB - This paper focuses on developing a team of mobile robots capable of learning via human interaction. A modified Q-learning algorithm incorporating a teacher is proposed. The paper first concentrates on simplifying the Q-learning algorithm to be implemented on small and simple team of robots having limited capabilities of memory and computational power. Second it concentrates on the incorporation of a human teacher in the Q-learning algorithm. Experiments using the well-known robot simulator Webots on both single and multi-target tracking tasks have been conducted. The achieved results show the success of the proposed algorithm in the over all system performance.
KW - Human-robot interaction
KW - Machine learning
KW - Q-learning
KW - Reinforcement learning
UR - http://www.scopus.com/inward/record.url?scp=67649544245&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=67649544245&partnerID=8YFLogxK
U2 - 10.1109/ICCES.2008.4772991
DO - 10.1109/ICCES.2008.4772991
M3 - Conference contribution
AN - SCOPUS:67649544245
SN - 9781424421152
SP - 173
EP - 178
BT - 2008 International Conference on Computer Engineering and Systems, ICCES 2008
ER -