Parameter search in an agent-based model of pedestrian movement in retail environments

Parameter search in an agent-based model of pedestrian movement in retail environments is part of a research effort by data-driven architecture in the Cognitive Machine Group at the MIT Media Lab. The approach pursued in this thesis is agent-based modeling, with an ultimate goal to use generative behaviors in agents to study effects of architectural and managerial decisions on retail environments. In this thesis, I designed and implemented an agent training module as a part of a software system which simulates and learns patterns of human pedestrian movement in retail environments. This thesis covers two different components: (1) the implementation of a hill-climbing training module and (2) a pedestrian path comparison metric. To measure the module's performance, the system is tested against video sequences collected from the actual retail environment.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2010

Author dc:creator

• Jitapunkul, Thananat

Advisor dc:contributor.advisor

• Deb K. Roy.

• Electrical Engineering and Computer Science.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/62656

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/62656