Multi-agent information classification using dynamic acquaintance lists-Reference-Cited by-同舟云学术

Multi-agent information classification using dynamic acquaintance lists

Published:2003 Issue:10 Volume:54 Page:966-975
ISSN:1532-2882
Container-title:Journal of the American Society for Information Science and Technology
language:en
Short-container-title:J. Am. Soc. Inf. Sci.

Author:

Mukhopadhyay Snehasis,Peng Shengquan,Raje Rajeev,Palakal Mathew,Mostafa Javed

Publisher

Wiley

Subject

Artificial Intelligence,Computer Networks and Communications,Human-Computer Interaction,Information Systems,Software

Reference19 articles.

1. (1996). Market-based control, Chapter 8?Metaphor or reality: a case study where agents bid with actual costs to schedule a factory, pages 184-223. World Scientific, River Edge, NJ.

2. Communications of the ACM. (1994). Special issue on intelligent agents. vol 37, 7.

3. & (1995). Macron: an architecture for multi-agent cooperative information gathering. Proceedings of CIKM Conference, Workshop on Intelligent Information Agents, Baltimore, MD.

4. & (1998). Intelligent collaborative information retrieval. Progress in Artificial Intelligence, IBERAMIA'98.

5. & (1989). Mice: a flexible testbed for intelligent coordination experiments. Proceedings of the 1989 Distributed Artificial Intelligence Workshop, pp. 25-40.

Cited by 9 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Learning improves service discovery;Concurrency and Computation: Practice and Experience;2014-07-04

2. Software Service Selection by Multi-level Matching and Reinforcement Learning;Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering;2012

3. Analyzing the Benefits of a Novel Multiagent Approach in a Multimodal Biometrics Identification Task;IEEE Systems Journal;2009-12

4. An Adaptive System for Home Monitoring Using a Multiagent Classification of Patterns;International Journal of Telemedicine and Applications;2008

5. Imagining, seeking, inventing: the future of learning and the emerging discovery networks;Learning Inquiry;2007-03-06