MAGS Project: Multi-agent GeoSimulation and Crowd Simulation

Moulin, Bernard; Chaker, Walid; Perron, Jimmy; Pelletier, Patrick; Hogan, Jimmy; Gbei, Edouard

doi:10.1007/978-3-540-39923-0_11

Cited by 43 publications

(63 citation statements)

References 17 publications

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“…Mand, Koch, and Moulin (Mand 2000, Koch 2001, Moulin et al 2003 presented multiagent geosimulation as a coupling of two technologies: the multiagent-based simulation (MABS) technology and the geographic information system (GIS). Based on the MABS technology, the simulated entities are represented by software agents that can be autonomous in their behavior.…”

Section: Geosimulation and Multiagent Geosimulationmentioning

confidence: 99%

“…According to our literature review, a small number of multiagent geosimulation platforms can be used to simulate systems in geographic environments using the agent paradigm. For example, we can cite the following platforms: common-pool resources and multiagent systems (CORMAS) (Bousquet et al 1998), multiagent geosimulation (MAGS) (Moulin et al 2003), and RePast (Dibble and Feldman, 2004) (Najlis and North, 2004). In our work, we use the MAGS platform to simulate the shopping behavior in a mall.…”

Section: Geosimulation and Multiagent Geosimulationmentioning

confidence: 99%

“…MAGS agents have several knowledge-based capabilities such as perception, navigation, memorization, communication, and objective-based behavior that allow them to display an autonomous behavior within a 2-D-3-D geographic virtual environment (Moulin et al 2003). The agents in MAGS are able to perceive the elements contained in the environment, to navigate autonomously inside it, and to react to changes occurring in the environment.…”

Section: The Mags Platformmentioning

confidence: 99%

“…The agents in MAGS are able to perceive the elements contained in the environment, to navigate autonomously inside it, and to react to changes occurring in the environment. These agents have several knowledge-based capabilities (Moulin et al 2003) that are briefly presented in the following paragraphs.…”

Section: The Mags Platformmentioning

confidence: 99%

“…In MAGS, agents can perceive (1) terrain characteristics such as elevations and slopes; (2) elements contained in the landscape surrounding them, including buildings and static objects; (3) other mobile agents navigating in the agent's range of perception; (4) dynamic areas or volumes whose shape changes during the simulation (for example, smoky areas or zones having pleasant odors); (5) spatial events such as explosions, etc., occurring in the agent's vicinity; and (6) messages communicated by other agents (Moulin et al 2003).…”

Section: The Mags Platformmentioning

confidence: 99%

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Active Transportation, Neighborhood Planning and Participatory GIS (Geographic Information System)

Schlossberg

Larco²

2008

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On the Cover:A common and humorous test of mental dexterity is the ability to walk and chew gum at the same time. These two simple tasks rarely conflict and are performed without thought. Over the past 10 years a new test of mental dexterity has arisen with vast implications in the field of geospatial technology; can one walk and collect data at the same time?Research on walking and the built environment has accelerated by an increased interest in the relationship between urban form and public health. As the research has progressed, so has the interest in developing ways to collect data at a very fine scale-in essence, to be able to collect data at the streetscape level and link this data to transportation behavior. An article by Marc Schlossberg, Asha Weinstein, and Katja Irvin entitled An Assessment of GISenabled Walkability Audits examines the development and implementation of a GIS-based pedestrian audit tool that allows users to collect data in electronic form using a handheld computer. The paper, which highlights Volume 19, Number 2 of the URISA Journal, identifies current shortcomings with walkability audit tools but concludes that appropriately applying GIS-enabled pedestrian audit tools can be an efficient way to collect and quickly analyze pedestrian infrastructure characteristics so that planners, practitioners, policy makers, and community members can make more effective decisions. SUBMISSIONS: This publication accepts from authors an exclusive right of first publication to their article plus an accompanying grant of nonexclusive full rights. The publisher requires that full credit for first publication in the URISA Journal is provided in any subsequent electronic or print publications. For more information, the "Manuscript Submission Guidelines for Refereed Articles" is available on our website, www.urisa. org, or by calling (847) 824-6300. SUBSCRIPTION AND ADVERTISING: All correspondence about advertising, subscriptions, and URISA memberships should be directed to: Urban and Regional Information Systems Association, 1460 Renaissance Dr., Suite 305, Park Ridge, Illinois, 60068-1348; Voice (847) 824-6300; Fax (847) 824-6363; E-mail info@urisa.org.URISA Journal is published two times a year by the Urban and Regional Information Systems Association.© 2007 by the Urban and Regional Information Systems Association. Authorization to photocopy items for internal or personal use, or the internal or personal use of specific clients, is granted by permission of the Urban and Regional Information Systems Association.Educational programs planned and presented by URISA provide attendees with relevant and rewarding continuing education experience. However, neither the content (whether written or oral) of any course, seminar, or other presentation, nor the use of a specific product in conjunction therewith, nor the exhibition of any materials by any party coincident with the educational event, should be construed as indicating endorsement or approval of the views presented, the products used, or the materials exhi...

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Section: Geosimulation and Multiagent Geosimulationmentioning

confidence: 99%

Section: Geosimulation and Multiagent Geosimulationmentioning

confidence: 99%

Section: The Mags Platformmentioning

confidence: 99%

Section: The Mags Platformmentioning

confidence: 99%

Section: The Mags Platformmentioning

confidence: 99%

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