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Comparison of MOMDP and heuristic methods to play hide-and-seek

Author
Goldhoorn, A.; Sanfeliu, A.; Alquezar, R.
Type of activity
Presentation of work at congresses
Name of edition
16th International Conference of the Catalan Association for Artificial Intelligence
Date of publication
2013
Presentation's date
2013-10-23
Book of congress proceedings
Artificial intelligence research and development: proceedings of the 16th International Conference of the Catalan Association for Artificial Intelligence
First page
31
Last page
40
DOI
10.3233/978-1-61499-320-9-31
URL
http://dx.doi.org/10.3233/978-1-61499-320-9-31 Open in new window
Abstract
The hide-and-seek game is considered an excellent domain for studying the interactions between mobile robots and humans. Prior to the implementation and test in our mobile robots TIBI and DABO, we have been devising different models and strategies to play this game and comparing them extensively in simulations. Recently, we have proposed the use of MOMDP (Mixed Observability Markov Decision Processes) models to learn a good policy to be applied by the seeker. Even though MOMDPs reduce the comput...
Keywords
POMDP, hide-and-Seek, human robot interaction, robotics
Group of research
SOCO - Soft Computing
VIS - Artificial Vision and Intelligent Systems

Participants