Robust agent communities

Sandip Sen; Sabyasachi Saha; Stéphane Airiau; Teddy Cándale; Dipyaman Banerjee; Doran Chakraborty; Partha Mukherjee; Anil Gursel

doi:10.1007/978-3-540-72839-9_3

Robust agent communities

Sandip Sen, Sabyasachi Saha, Stéphane Airiau, Teddy Cándale, Dipyaman Banerjee, Doran Chakraborty, Partha Mukherjee, Anil Gursel

Engineering Division (Great Valley)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Scopus citations

Abstract

We believe that intelligent information agents will represent their users interest in electronic marketplaces and other forums to trade, exchange, share, identify, and locate goods and services. Such information worlds will present unforeseen opportunities as well as challenges that can be best addressed by robust, self-sustaining agent communities. An agent community is a stable, adaptive group of self-interested agents that share common resources and must coordinate their efforts to effectively develop, utilize and nurture group resources and organization. More specifically, agents will need mechanisms to benefit from complementary expertise in the group, pool together resources to meet new demands and exploit transient opportunities, negotiate fair settlements, develop norms to facilitate coordination, exchange help and transfer knowledge between peers, secure the community against intruders, and learn to collaborate effectively. In this talk, I will summarize some of our research results on trust-based computing, negotiation, and learning that will enable intelligent agents to develop and sustain robust, adaptive, and successful agent communities.

Original language	English (US)
Title of host publication	Autonomous Intelligent Systems
Subtitle of host publication	Agents and Data Mining - Second International Workshop, AIS-ADM 2007, Proceedings
Publisher	Springer Verlag
Pages	28-45
Number of pages	18
ISBN (Print)	9783540728382
DOIs	https://doi.org/10.1007/978-3-540-72839-9_3
State	Published - 2007
Event	2nd International Workshop Autonomous Intelligent Systems: Agents and Data Mining, AIS-ADM 2007 - St. Petersburg, Russian Federation Duration: Jun 3 2007 → Jun 5 2007

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	4476 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	2nd International Workshop Autonomous Intelligent Systems: Agents and Data Mining, AIS-ADM 2007
Country/Territory	Russian Federation
City	St. Petersburg
Period	6/3/07 → 6/5/07

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-540-72839-9_3

Cite this

Sen, S., Saha, S., Airiau, S., Cándale, T., Banerjee, D., Chakraborty, D., Mukherjee, P., & Gursel, A. (2007). Robust agent communities. In Autonomous Intelligent Systems: Agents and Data Mining - Second International Workshop, AIS-ADM 2007, Proceedings (pp. 28-45). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4476 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-540-72839-9_3

@inproceedings{c59b53d2776b47e59fe7014d5ca7bc31,

title = "Robust agent communities",

abstract = "We believe that intelligent information agents will represent their users interest in electronic marketplaces and other forums to trade, exchange, share, identify, and locate goods and services. Such information worlds will present unforeseen opportunities as well as challenges that can be best addressed by robust, self-sustaining agent communities. An agent community is a stable, adaptive group of self-interested agents that share common resources and must coordinate their efforts to effectively develop, utilize and nurture group resources and organization. More specifically, agents will need mechanisms to benefit from complementary expertise in the group, pool together resources to meet new demands and exploit transient opportunities, negotiate fair settlements, develop norms to facilitate coordination, exchange help and transfer knowledge between peers, secure the community against intruders, and learn to collaborate effectively. In this talk, I will summarize some of our research results on trust-based computing, negotiation, and learning that will enable intelligent agents to develop and sustain robust, adaptive, and successful agent communities.",

author = "Sandip Sen and Sabyasachi Saha and St{\'e}phane Airiau and Teddy C{\'a}ndale and Dipyaman Banerjee and Doran Chakraborty and Partha Mukherjee and Anil Gursel",

year = "2007",

doi = "10.1007/978-3-540-72839-9_3",

language = "English (US)",

isbn = "9783540728382",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "28--45",

booktitle = "Autonomous Intelligent Systems",

address = "Germany",

note = "2nd International Workshop Autonomous Intelligent Systems: Agents and Data Mining, AIS-ADM 2007 ; Conference date: 03-06-2007 Through 05-06-2007",

}

Sen, S, Saha, S, Airiau, S, Cándale, T, Banerjee, D, Chakraborty, D, Mukherjee, P & Gursel, A 2007, Robust agent communities. in Autonomous Intelligent Systems: Agents and Data Mining - Second International Workshop, AIS-ADM 2007, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4476 LNAI, Springer Verlag, pp. 28-45, 2nd International Workshop Autonomous Intelligent Systems: Agents and Data Mining, AIS-ADM 2007, St. Petersburg, Russian Federation, 6/3/07. https://doi.org/10.1007/978-3-540-72839-9_3

Robust agent communities. / Sen, Sandip; Saha, Sabyasachi; Airiau, Stéphane et al.
Autonomous Intelligent Systems: Agents and Data Mining - Second International Workshop, AIS-ADM 2007, Proceedings. Springer Verlag, 2007. p. 28-45 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4476 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Robust agent communities

AU - Sen, Sandip

AU - Saha, Sabyasachi

AU - Airiau, Stéphane

AU - Cándale, Teddy

AU - Banerjee, Dipyaman

AU - Chakraborty, Doran

AU - Mukherjee, Partha

AU - Gursel, Anil

PY - 2007

Y1 - 2007

N2 - We believe that intelligent information agents will represent their users interest in electronic marketplaces and other forums to trade, exchange, share, identify, and locate goods and services. Such information worlds will present unforeseen opportunities as well as challenges that can be best addressed by robust, self-sustaining agent communities. An agent community is a stable, adaptive group of self-interested agents that share common resources and must coordinate their efforts to effectively develop, utilize and nurture group resources and organization. More specifically, agents will need mechanisms to benefit from complementary expertise in the group, pool together resources to meet new demands and exploit transient opportunities, negotiate fair settlements, develop norms to facilitate coordination, exchange help and transfer knowledge between peers, secure the community against intruders, and learn to collaborate effectively. In this talk, I will summarize some of our research results on trust-based computing, negotiation, and learning that will enable intelligent agents to develop and sustain robust, adaptive, and successful agent communities.

AB - We believe that intelligent information agents will represent their users interest in electronic marketplaces and other forums to trade, exchange, share, identify, and locate goods and services. Such information worlds will present unforeseen opportunities as well as challenges that can be best addressed by robust, self-sustaining agent communities. An agent community is a stable, adaptive group of self-interested agents that share common resources and must coordinate their efforts to effectively develop, utilize and nurture group resources and organization. More specifically, agents will need mechanisms to benefit from complementary expertise in the group, pool together resources to meet new demands and exploit transient opportunities, negotiate fair settlements, develop norms to facilitate coordination, exchange help and transfer knowledge between peers, secure the community against intruders, and learn to collaborate effectively. In this talk, I will summarize some of our research results on trust-based computing, negotiation, and learning that will enable intelligent agents to develop and sustain robust, adaptive, and successful agent communities.

UR - http://www.scopus.com/inward/record.url?scp=38049184631&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=38049184631&partnerID=8YFLogxK

U2 - 10.1007/978-3-540-72839-9_3

DO - 10.1007/978-3-540-72839-9_3

M3 - Conference contribution

AN - SCOPUS:38049184631

SN - 9783540728382

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 28

EP - 45

BT - Autonomous Intelligent Systems

PB - Springer Verlag

T2 - 2nd International Workshop Autonomous Intelligent Systems: Agents and Data Mining, AIS-ADM 2007

Y2 - 3 June 2007 through 5 June 2007

ER -

Sen S, Saha S, Airiau S, Cándale T, Banerjee D, Chakraborty D et al. Robust agent communities. In Autonomous Intelligent Systems: Agents and Data Mining - Second International Workshop, AIS-ADM 2007, Proceedings. Springer Verlag. 2007. p. 28-45. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-72839-9_3

Robust agent communities

Abstract

Publication series

Conference

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this