Segmentation of environments using hidden Markov modeling of other agents

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Segmentation of environments using hidden Markov modeling of other agents

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International Conference on Autonomous Agents archive
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 3 table of contents

Bologna, Italy

SESSION: Session 9D: embodied agents table of contents

Pages: 1395 - 1396

Year of Publication: 2002

ISBN:1-58113-480-0

Author

Itsuki NODA

Itsuki Cyber Assist Research Center, AIST and PRESTO, JST, Tokyo, Japan

Sponsors

ACM: Association for Computing Machinery
SIGART: ACM Special Interest Group on Artificial Intelligence

Publisher

ACM New York, NY, USA

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REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	P. Bakker and Y. Kuniyoshi. Robot see, robot do: An overview of robot imitation. In Proc of AISB96 Workshop: Learning in Robots and 1996.
	2	Y. Bengio and P. Frasconi. An input output hmm architecuture. In G. Tesauro,D. Touretzky, and T. Leen, editors, Advances in Neural Information Processing pages 427 -434. The MIT Press, 1995.
	3	M. I. Jordan, Z. Ghahramani, and L. K. Saul. Hidden markov decision trees. In M. C. Mozer, M. I. Jordan, and T. Petsche, editors, Advances in Neural Information Processing volume 9, page 501. The MIT Press, 1997.
	4	I. Noda. Learning method by overload. In IJCNN'93-pages 1357--1360, Oct. 1993.
	5	I. NODA. Hidden markov modeling of multi-agent systems and its learning method. In Proc. of RoboCup 2002 International 2002.
	6	S. Schaal. Is imitation learning the route to humanoid robots? Trends in Cognitive 3(6):233--242, Jun. 1999.