Individual Civil Building Intelligent Project Design Based on the Agent

Xin Xu; Fang Li

doi:10.4028/www.scientific.net/AMM.568-570.863

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 568-570Individual Civil Building Intelligent Project...

Individual Civil Building Intelligent Project Design Based on the Agent

Abstract:

Individual civil building intelligent project design is the process of using the artificial intelligence Agent technology in simulation the three logical relationship of building user, bubbles, streamline. Divided by bubbles, streamline generation and adjustment, bubbles divided again, streamline refinement and adjustment, until the last bubble becomes a specific room, streamline into specific hall gallery, generate the corresponding construction main body structure finally change into figure according to national building drawing standards, so completed the design of intelligent optimization and scheme evaluation with real-time interaction. Intelligent design process is an innovation in the field of computer aided architectural design, shorten the design time and improve the design efficiency.

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Periodical:

Applied Mechanics and Materials (Volumes 568-570)

Pages:

863-867

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.568-570.863

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Online since:

June 2014

Authors:

Xin Xu, Fang Li

Keywords:

Agent, Artificial Intelligence (AI), Project Design, Streamline Analysis

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References

[1] Michael Wooldridge: The logical modeling of computational multi-agent systems. Manchester UK (Manchester university, 1992).

Google Scholar

[2] S. Russell, P. Norving: Artificial Intelligence: A modern Approach( Pretice Hall, 1995).

Google Scholar

[3] Y. Shoham,M. Tenenholtz: Agent-Oriented Programming. Artificial Intelligence, Elsevir Science Publisher B. Vol. 60(1993), pp.51-92.

DOI: 10.1016/0004-3702(93)90034-9

Google Scholar

[4] Manuel Kolp, Paolo Giorgini, John Mylopoulos: Multi-agent architectures as organizational structures. Journal of Autonomous Agent and Multi-Agent System, Vol. 13(2006), pp.3-25.

DOI: 10.1007/s10458-006-5717-6

Google Scholar

[5] R. Nicholas, Jennings, Michael: Wooldridge. Agent-Oriented Software Engineering, J. Bradshaw, editor, Handbook of Agent Technology. AAAI/MIT Press(2002).

Google Scholar

[6] Philippe Massonet: From AOSE methodology to agent implementation, Proeeedings of the first international joint conference on Autonomous agent and multiagent systems(2002), pp.27-34.

DOI: 10.1145/544741.544747

Google Scholar

[7] Conor, Brendan Ward: Brian Henderson-Sellers. Utilizing Dynamic Roles for Agents. Journal of Object Technology, Vol. 8(2009), pp.177-198.

Google Scholar

[8] David V Pynadath, Milind Tanbe: An Automated Teamwork Infrastructure for Heterogeneous Software Agents and Humans. Autonomous Agents and Multi-Agent Systems, Vol. 7(2003), pp.71-100.

Google Scholar

[9] T. Abdelaziz, M. Elammari,R. Unland. MASD: Multi-agent systems development methodology. Journal Multiagent and Grid Systems, Vol. 6(2010), pp.71-101.

DOI: 10.3233/mgs-2010-0142

Google Scholar