Using decision tree confidence factors for multi-agent control

Subscribe (Full Service)


	Search: The ACM Digital Library The Guide

	Feedback

Using decision tree confidence factors for multi-agent control

Full text

Pdf (850 KB)

Source

International Conference on Autonomous Agents archive
Proceedings of the second international conference on Autonomous agents table of contents

Minneapolis, Minnesota, United States

Pages: 86 - 91

Year of Publication: 1998

ISBN:0-89791-983-1

Authors

Peter Stone	Computer Science Department, Carnegie Mellon University, Pittsburgh, PA
Manuela Veloso	Computer Science Department, Carnegie Mellon University, Pittsburgh, PA

Sponsors

IEEE : Institute of Electrical and Electronics Engineers
SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques
SIGART: ACM Special Interest Group on Artificial Intelligence
SIGCHI: ACM Special Interest Group on Computer-Human Interaction

Publisher

ACM New York, NY, USA

Bibliometrics

Downloads (6 Weeks): 8, Downloads (12 Months): 40, Citation Count: 4

Additional Information:

references cited by index terms collaborative colleagues

Tools and Actions:	Review this Article Save this Article to a Binder Display Formats: BibTeX EndNote ACM Ref

DOI Bookmark:	Use this link to bookmark this Article: http://doi.acm.org/10.1145/280765.280780 What is a DOI?

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	Minoru Asada, Eiji Uchibe, Shoichi Noda, Sukoya Tawaratsumida, and Koh Hosoda. Coordination of multiple behaviors acquired by vision-based reinforcement learning, In Proc, of IEEE/RSJ/GI International Conference on Intelligent Robots and Systems 1994 (IROS 19d), pages 917-924, 1994.
	2	Mike Bowling, Peter Stone, and Manuela Veloso. Predictive memory for an inaccessible environment. In Pro. ceedings of the {ROS-96 Workshop on RoboCup, pages 28-34, Osaka, Japan, November 1996.
	3	Andrew Garland and Richard Alterman. Multiagent learning through collective memory. In Adaptation, Co. evolution and Learning in Multiagent Systems: Papers from the 1996 AAA{ Spring Symposium, pages 33-38, Menlo Park,CA, March 1996. AAAI Press. AAAI Technical Report SS-96-01.
	4	Jong-Hwan Kim, editor. Proceedings of the Micro-Robot World Cup Soccer Tournament, Taejon, Korea, November 1996.
	5	ttiroaki Kitano, Yasuo Kuniyoshi, Itsuki Noda, Minoru Asada, Hitoshi Matsubara, and Eiichi Osawa. RoboCup: A challenge problem for AI. Air Magazine, 18(1):73-85, Spring 1997.
	6	Hitoshi Matsubara, Itsuld Node, and Kazuo Hiraki. Learning of cooperative actions in multi-agent systems: a case study of pass play in soccer. In Adaptation, Co. evolution and Learning in Multiagent Systems: Papers from the 1996 AAAir Spring Symposium, pages 63--67, Menlo Park, CA, March 1996. AAAI Press. AAAI Technical Report SS-96-01.
	7	Itstttd Nods and Hitoshi Matsubara. Soccer server and researches on multi-agent systems. In Proceedings of the IROS-96 Workshop on RoboCup, November 1996.
	8	J. Ross Quinlan, C4.5: programs for machine learning, Morgan Kaufmann Publishers Inc., San Francisco, CA, 1993
	9	Michael K. Sabots. Dynasim user guide.
	10	Michael K. Sahota, Alan K. Mackworth, Rod A. Barman, and Stewart J. Kingdom Real-time control of soccer-playing robots using off-board vision: the dynamite testbed. In IEEE International Conference on Systems, Man, and Cybernetics, pages 3690-3663, 1995,
	11	Randy Sargent, Bill Bailey, Carl Witty, and Anne Wright. Dynamic object capture using fast vision tracking. Air Magazine, 18(1):65-72, Spring 1997.
	12	Peter Stone and Manuela Veloso. Beating a defender in robotic soccer: Memory-based learning of a continuous function. In David S. Touretzky, Michael C. Mozer, and Michael E. Hasselmo, editors, Advances in Neu. ral irnformation Processing Systems 8, pages 896-902, Cambridge, MA, 1996. MIT Press.
	13	Peter Stone and Manuela Veloso. A layered approach to learning client behaviors in the RoboCup soccer server. Applied Artificial Intelligence, 12, 1998. In Press.
	14	Peter Stone , Manuela Veloso, Towards collaborative and adversarial learning:: a case study in robotic soccer, International Journal of Human-Computer Studies, v.48 n.1, p.83-104, Jan., 1998 [doi>10.1006/ijhc.1997.0162]
	15	Manuela M. Veloso , Peter Stone , Kwun Han , Sorin Achim, The CMUnited-97 Small Robot Team, RoboCup-97: Robot Soccer World Cup I, p.242-256, January 1998

CITED BY 4

	Peter Stone , Manuela Veloso, Team-partitioned, opaque-transition reinforcement learning, Proceedings of the third annual conference on Autonomous Agents, p.206-212, April 1999, Seattle, Washington, United States
	Taylor Raines , Milind Tambe , Stacy Marsella, Automated assistants to aid humans in understanding team behaviors, Proceedings of the fourth international conference on Autonomous agents, p.419-426, June 03-07, 2000, Barcelona, Spain
	Ranjit Nair , Milind Tambe , Stacy Marsella , Taylor Raines, Automated Assistants for Analyzing Team Behaviors, Autonomous Agents and Multi-Agent Systems, v.8 n.1, p.69-111, January 2004
	Geoff Nitschke, Emergence of Cooperation: State of the Art, Artificial Life, v.11 n.3, p.367-396, September 2005