Standard
Agent teams for design problems. /
Soriano Marcolino, Leandro; Xu, Haifeng; Gerber, David J. et al.
19th International Workshop on Coordination, Organisations, Institutions and Norms (COIN 2015). ed. / Pablo Noriega; Murat Sensoy. AAMAS, 2015. p. 189-204.
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Harvard
Soriano Marcolino, L, Xu, H, Gerber, DJ, Kolev, B, Price, S, Pantazis, E & Tambe, M 2015,
Agent teams for design problems. in P Noriega & M Sensoy (eds),
19th International Workshop on Coordination, Organisations, Institutions and Norms (COIN 2015). AAMAS, pp. 189-204. <
http://coin-aamas2015.iiia.csic.es/NiceCOINProceedings.pdf>
APA
Soriano Marcolino, L., Xu, H., Gerber, D. J., Kolev, B., Price, S., Pantazis, E., & Tambe, M. (2015).
Agent teams for design problems. In P. Noriega, & M. Sensoy (Eds.),
19th International Workshop on Coordination, Organisations, Institutions and Norms (COIN 2015) (pp. 189-204). AAMAS.
http://coin-aamas2015.iiia.csic.es/NiceCOINProceedings.pdf
Vancouver
Soriano Marcolino L, Xu H, Gerber DJ, Kolev B, Price S, Pantazis E et al.
Agent teams for design problems. In Noriega P, Sensoy M, editors, 19th International Workshop on Coordination, Organisations, Institutions and Norms (COIN 2015). AAMAS. 2015. p. 189-204
Author
Bibtex
@inproceedings{9e04aa67ac0440d089d7ef3fdebceb61,
title = "Agent teams for design problems",
abstract = "Design imposes a novel social choice problem: using a team of voting agents, maximize the number of optimal solutions; allowing a user to then take an aesthetical choice. In an open system of design agents, team formation is fundamental. We present the first model of agent teams for design. For maximum applicability, we envision agents that are queried for a single opinion, and multiple solutions are obtained by multiple iterations. We show that diverse teams composed of agents with different preferences maximize the number of optimal solutions, while uniform teams composed of multiple copies of the best agent are in general suboptimal. Our experiments study the model in bounded time; and we also study a real system, where agents vote to design buildings",
keywords = "Collaboration, Distributed AI, Team Formation",
author = "{Soriano Marcolino}, Leandro and Haifeng Xu and Gerber, {David J.} and Boian Kolev and Samori Price and Evangelos Pantazis and Milind Tambe",
year = "2015",
month = may,
day = "4",
language = "English",
pages = "189--204",
editor = "Pablo Noriega and Murat Sensoy",
booktitle = "19th International Workshop on Coordination, Organisations, Institutions and Norms (COIN 2015)",
publisher = "AAMAS",
}
RIS
TY - GEN
T1 - Agent teams for design problems
AU - Soriano Marcolino, Leandro
AU - Xu, Haifeng
AU - Gerber, David J.
AU - Kolev, Boian
AU - Price, Samori
AU - Pantazis, Evangelos
AU - Tambe, Milind
PY - 2015/5/4
Y1 - 2015/5/4
N2 - Design imposes a novel social choice problem: using a team of voting agents, maximize the number of optimal solutions; allowing a user to then take an aesthetical choice. In an open system of design agents, team formation is fundamental. We present the first model of agent teams for design. For maximum applicability, we envision agents that are queried for a single opinion, and multiple solutions are obtained by multiple iterations. We show that diverse teams composed of agents with different preferences maximize the number of optimal solutions, while uniform teams composed of multiple copies of the best agent are in general suboptimal. Our experiments study the model in bounded time; and we also study a real system, where agents vote to design buildings
AB - Design imposes a novel social choice problem: using a team of voting agents, maximize the number of optimal solutions; allowing a user to then take an aesthetical choice. In an open system of design agents, team formation is fundamental. We present the first model of agent teams for design. For maximum applicability, we envision agents that are queried for a single opinion, and multiple solutions are obtained by multiple iterations. We show that diverse teams composed of agents with different preferences maximize the number of optimal solutions, while uniform teams composed of multiple copies of the best agent are in general suboptimal. Our experiments study the model in bounded time; and we also study a real system, where agents vote to design buildings
KW - Collaboration
KW - Distributed AI
KW - Team Formation
M3 - Conference contribution/Paper
SP - 189
EP - 204
BT - 19th International Workshop on Coordination, Organisations, Institutions and Norms (COIN 2015)
A2 - Noriega, Pablo
A2 - Sensoy, Murat
PB - AAMAS
ER -
