Subject: Pedestrian modeling · Bayesian inference · Multi-agent simulation
Year: 2017
Type: Proceeding article
Title: Knowledge-Based Approach to Modeling Urban Dynamics
Author: Gievska, Sonja
Author: Lameski, Petre
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.
Publisher: Springer, Cham
Relation: International Conference on Distributed, Ambient, and Pervasive Interactions
Identifier: oai:repository.ukim.mk:20.500.12188/22377
Identifier: http://hdl.handle.net/20.500.12188/22377
