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Agents vote for the environment: designing energy-efficient architecture

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

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Agents vote for the environment: designing energy-efficient architecture. / Soriano Marcolino, Leandro; Gerber, David J.; Kolev, Boian et al.
AAAI Workshop on Computational Sustainability (AAAI 2015). 2015.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Soriano Marcolino, L, Gerber, DJ, Kolev, B, Price, S, Pantazis, E, Tiam, Y & Tambe, M 2015, Agents vote for the environment: designing energy-efficient architecture. in AAAI Workshop on Computational Sustainability (AAAI 2015).

APA

Soriano Marcolino, L., Gerber, D. J., Kolev, B., Price, S., Pantazis, E., Tiam, Y., & Tambe, M. (2015). Agents vote for the environment: designing energy-efficient architecture. In AAAI Workshop on Computational Sustainability (AAAI 2015)

Vancouver

Soriano Marcolino L, Gerber DJ, Kolev B, Price S, Pantazis E, Tiam Y et al. Agents vote for the environment: designing energy-efficient architecture. In AAAI Workshop on Computational Sustainability (AAAI 2015). 2015

Author

Soriano Marcolino, Leandro ; Gerber, David J. ; Kolev, Boian et al. / Agents vote for the environment : designing energy-efficient architecture. AAAI Workshop on Computational Sustainability (AAAI 2015). 2015.

Bibtex

@inproceedings{b85ef926ceda4c4bbe81b4b6dbaa1716,
title = "Agents vote for the environment: designing energy-efficient architecture",
abstract = "Saving energy is a major concern. Hence, it is fundamental to design and construct buildings that are energy-efficient. It is known that the early stage of architectural design has a significant impact on this matter.However, it is complex to create designs that are optimally energy efficient, and at the same time balance other essential criterias such as economics, space, and safety. One state-of-the art approach is to create parametric designs, and use a genetic algorithm to optimizeacross different objectives. We further improve this method, by aggregating the solutions of multiple agents. We evaluate diverse teams, composed by different agents; and uniform teams, composed by multiple copies of a single agent. We test our approach across three design cases of increasing complexity, and show that the diverse team provides a significantly larger percentageof optimal solutions than single agents.",
author = "{Soriano Marcolino}, Leandro and Gerber, {David J.} and Boian Kolev and Samori Price and Evangelos Pantazis and Ye Tiam and Milind Tambe",
year = "2015",
language = "English",
booktitle = "AAAI Workshop on Computational Sustainability (AAAI 2015)",

}

RIS

TY - GEN

T1 - Agents vote for the environment

T2 - designing energy-efficient architecture

AU - Soriano Marcolino, Leandro

AU - Gerber, David J.

AU - Kolev, Boian

AU - Price, Samori

AU - Pantazis, Evangelos

AU - Tiam, Ye

AU - Tambe, Milind

PY - 2015

Y1 - 2015

N2 - Saving energy is a major concern. Hence, it is fundamental to design and construct buildings that are energy-efficient. It is known that the early stage of architectural design has a significant impact on this matter.However, it is complex to create designs that are optimally energy efficient, and at the same time balance other essential criterias such as economics, space, and safety. One state-of-the art approach is to create parametric designs, and use a genetic algorithm to optimizeacross different objectives. We further improve this method, by aggregating the solutions of multiple agents. We evaluate diverse teams, composed by different agents; and uniform teams, composed by multiple copies of a single agent. We test our approach across three design cases of increasing complexity, and show that the diverse team provides a significantly larger percentageof optimal solutions than single agents.

AB - Saving energy is a major concern. Hence, it is fundamental to design and construct buildings that are energy-efficient. It is known that the early stage of architectural design has a significant impact on this matter.However, it is complex to create designs that are optimally energy efficient, and at the same time balance other essential criterias such as economics, space, and safety. One state-of-the art approach is to create parametric designs, and use a genetic algorithm to optimizeacross different objectives. We further improve this method, by aggregating the solutions of multiple agents. We evaluate diverse teams, composed by different agents; and uniform teams, composed by multiple copies of a single agent. We test our approach across three design cases of increasing complexity, and show that the diverse team provides a significantly larger percentageof optimal solutions than single agents.

M3 - Conference contribution/Paper

BT - AAAI Workshop on Computational Sustainability (AAAI 2015)

ER -