Knowledge-Based Approach to Modeling Urban Dynamics
Date Issued
2017-07-09
Author(s)
Abstract
The model representing the complexity of the pedestrian mobility has
to incorporate the nature of the modeled phenomenon by accounting the interde‐
pendence between human behavior and urban environment. Our efforts are
directed towards correlating emergent behavior patterns of different types of
pedestrians to contextual knowledge that will help us map realistic pedestrian
behavior into agent’s decision making capabilities. We propose that agent’s
beliefs, goals and decision-making strategies should be derived directly from the
integrated urban knowledge. Causal probabilistic models that are based on Baye‐
sian inference are proposed as a potential solution to some of the challenges in
the pedestrian agent modeling.
to incorporate the nature of the modeled phenomenon by accounting the interde‐
pendence between human behavior and urban environment. Our efforts are
directed towards correlating emergent behavior patterns of different types of
pedestrians to contextual knowledge that will help us map realistic pedestrian
behavior into agent’s decision making capabilities. We propose that agent’s
beliefs, goals and decision-making strategies should be derived directly from the
integrated urban knowledge. Causal probabilistic models that are based on Baye‐
sian inference are proposed as a potential solution to some of the challenges in
the pedestrian agent modeling.
Subjects
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