Article

BIG: a resource-bounded information gathering agent

Authors:

Frank Klassner,

Anita RajaAuthors Info & Claims

AAAI '98/IAAI '98: Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence

Pages 539 - 546

Published: 01 July 1998 Publication History

Abstract

Effective information gathering on the WWW is a complex task requiring planning, scheduling, text processing, and interpretation-style reasoning about extracted data to resolve inconsistencies and to refine hypotheses about the data. This paper describes the rationale, architecture, and implementation of a next generation information gathering system - a system that integrates several areas of AI research under a single research umbrella. The goal of this system is to exploit the vast number of information sources available today on the NII including a growing number of digital libraries, independent news agencies, government agencies, as well as human experts providing a variety of services. The large number of information sources and their different levels of accessibility, reliability and associated costs present a complex information gathering coordination problem. Our solution is an information gathering agent, BIG, that plans to gather information to support a decision process, reasons about the resource tradeoffs of different possible gathering approaches, extracts information from both unstructured and structured documents. and uses the extracted information to refine its search and processing activities.

References

[1]

Callan, J. P.; Croft, W. B.; and Harding, S. M. 1992. The INQUERY retrieval system. In Proceedings of the 3rd Intl. Conf. on Database and Expert Systems Applications , 78- 83.

[2]

Callan, J. P. 1996. Document filtering with inference networks. In Proceedings of the 19th Intl. ACM SIGIR Conference on Research and Development in Information Retrieval , 262-269.

[3]

Carver, N., and Lesser, V. 1991. A new framework for sensor interpretation: Planning to resolve sources of uncertainty. In Proceedings of the Ninth National Conference on Artificial Intelligence , 724-731.

[4]

Carver, N., and Lesser, V. 1995. The DRESUN testbed for research in FA/C distributed situation assessment: Extensions to the model of external evidence. In Proceedings of the 1st Intl. Conf. on Multiagent Systems .

[5]

Cowie, J., and Lehnert, W. 1996. Information extraction. Communications of the ACM 39(1):80-91.

[6]

Dean, T., and Boddy, M. 1988. An analysis of time-dependent planning. In Proceedings of the Seventh National Conference on Artificial Intelligence , 49-54.

[7]

Decker, K S., and Lesser, V. R. 1993. Quantitative modeling of complex environments. International Journal of Intelligent Systems in Accounting, Finance, and Management 2(4):215-234.

[8]

Decker, K.; Pannu, A.; Sycara, K.; and Williamson, M. 1997. Designing behaviors for information agents. In Proceedings of the 1st Intl. Conf. on Autonomous Agents , 404- 413.

[9]

Decker, K S. 1996. Task environment centered simulation. In Prietula, M.; Carley, K.; and Gasser, L., eds., Simulating Organizations: Computational Models of Institutions and Groups . AAAI Press/MIT Press.

[10]

Doorenbos, R.; Etzioni, O.; and Weld, D. 1997. A scalable comparision-shopping agent for the world-wide-web. In Proceedings of the 1st Intl. Conf. on Autonomous Agents , 39-48.

[11]

Etzioni, O.; Hanks, S.; Jiang, T.; Karp, R.; Madani, O.; and Waarts, O. 1996. Optimal information gathering on the internet with time and cost constraints. In Proceedings of the Thirty-seventh IEEE Symposium on Foundations of Computer Science (FOCS) .

[12]

Horvitz, E.; Cooper, G.; and Heckerman, D. 1989. Reflection and action under scarce resources: Theoretical principles and empirical study. In Proceedings of the 11th Intl. Joint Conf. on Artificial Intelligence .

[13]

Krulwich, B. 1996. The BargainFinder Agent: Comparison price shopping on the Internet. In Williams, J., ed., Bots and Other Internet Beasties . SAMS.NET. http://bf.cstar.ac.com/bf/.

[14]

Larkey, L., and Croft, W. B. 1996. Combining classifiers in text categorization. In Proceedings of the 19th Intl. Conf. on Research and Development in information Retrieval (SIGIR '96) , 289-297.

[15]

Lehnert, W., and Sundheim, B. 1991. A performance evaluation of text analysis technologies. AI Magazine 12(3):81- 94.

[16]

Russell, S. J., and Zilberstein, S. 1991. Composing realtime systems. In Proceedings of the 12th Intl. Joint Conf. on Artificial Intelligence , 212-217.

[17]

Soderland, S.; Fisher, D.; Aseltine, J.; and Lehnert, W. 1995. Crystal: Inducing a conceptual dictionary. In Proceedings of the 14th Intl. Joint Conf. on Artificial Intelligence , 1314-1321.

[18]

Wagner, T.; Garvey, A.; and Lesser, V. 1997. Complex Goal Criteria and Its Application in Design-to-Criteria Scheduling. In Proceedings of the 14th National Conf. on Artificial Intelligence , 294-301.

[19]

Wagner, T.; Garvey, A.; and Lesser, V. 1998. Criteria-Directed Heuristic Task Scheduling. Internarional Journal of Approximate Reasoning, Special Issue on Scheduling .

[20]

Wellmen, M.; Durfee, E.; and Birmingham, W. 1996. The digital library as community of information agents. IEEE Expert .

Cited By

Choi WStvilia BBouthillier FJu B(2013)Use of mobile wellness applications and perception of qualityProceedings of the 76th ASIS&T Annual Meeting: Beyond the Cloud: Rethinking Information Boundaries10.5555/2655780.2655928(1-4)Online publication date: 1-Nov-2013
https://dl.acm.org/doi/10.5555/2655780.2655928
Wang XZhang SKiliccote PSierra CGini MRosenschein J(2000)Anytime algorithm for agent-mediated merchant information gatheringProceedings of the fourth international conference on Autonomous agents10.1145/336595.337518(333-340)Online publication date: 1-Jun-2000
https://dl.acm.org/doi/10.1145/336595.337518
Raja ALesser VWagner TSierra CGini MRosenschein J(2000)Toward robust agent control in open environmentsProceedings of the fourth international conference on Autonomous agents10.1145/336595.337054(84-91)Online publication date: 1-Jun-2000
https://dl.acm.org/doi/10.1145/336595.337054
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BIG: a resource-bounded information gathering agent

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Information & Contributors

Information

Published In

cover image Guide Proceedings

AAAI '98/IAAI '98: Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence

July 1998

1218 pages

ISBN:0262510987

Chairmen:
Jack Mostow
Carnegie Mellon Univ., Pittsburgh, PA
,
Charles Rich
Mitsubishi Electric Research Lab
,
Bruce Buchanan
Mitsubishi Electric Research Lab

Publisher

American Association for Artificial Intelligence

United States

Publication History

Published: 01 July 1998

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Cited By

Choi WStvilia BBouthillier FJu B(2013)Use of mobile wellness applications and perception of qualityProceedings of the 76th ASIS&T Annual Meeting: Beyond the Cloud: Rethinking Information Boundaries10.5555/2655780.2655928(1-4)Online publication date: 1-Nov-2013
https://dl.acm.org/doi/10.5555/2655780.2655928
Wang XZhang SKiliccote PSierra CGini MRosenschein J(2000)Anytime algorithm for agent-mediated merchant information gatheringProceedings of the fourth international conference on Autonomous agents10.1145/336595.337518(333-340)Online publication date: 1-Jun-2000
https://dl.acm.org/doi/10.1145/336595.337518
Raja ALesser VWagner TSierra CGini MRosenschein J(2000)Toward robust agent control in open environmentsProceedings of the fourth international conference on Autonomous agents10.1145/336595.337054(84-91)Online publication date: 1-Jun-2000
https://dl.acm.org/doi/10.1145/336595.337054
Lesser VHorling BRaja AZhang XWagner T(2000)Resource-Bounded Searches in an Information MarketplaceIEEE Internet Computing10.1109/4236.8329464:2(49-58)Online publication date: 1-Mar-2000
https://dl.acm.org/doi/10.1109/4236.832946
Lesser VAtighetchi MBenyo BHorling BRaja AVincent RWagner TXuan PZhang S(1999)The UMASS intelligent home projectProceedings of the third annual conference on Autonomous Agents10.1145/301136.301213(291-298)Online publication date: 1-Apr-1999
https://dl.acm.org/doi/10.1145/301136.301213
Lesser V(1998)Reflections on the Nature of Multi-Agent Coordination and Its Implications for an Agent ArchitectureAutonomous Agents and Multi-Agent Systems10.1023/A:10100466230131:1(89-111)Online publication date: 1-Jan-1998
https://dl.acm.org/doi/10.1023/A%3A1010046623013

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