Xiaoshan Pan

TL;DR: This paper presents a multi-agent based framework for simulating human and social behavior during emergency evacuation, which is able to demonstrate some emergent behaviors, such as competitive, queuing, and herding behaviors.

TL;DR: In this paper, the authors present a framework for studying human and social behavior from the perspectives of human decision-making and social interaction, and for incorporating such behavior systematically in a dynamic computational model suitable for emergency evacuation and egress analysis.

TL;DR: This dissertation addresses the problem of bringing the perspectives of psychology and sociology about human behavior in emergencies into computational models for egress analysis by incorporation of diverse human behavior into a Multi-Agent Simulation System for Egress analysis (MASSEgress).

TL;DR: This paper presents a multi-agent based framework for studying human and social behavior during building emergency evacuations, and a prototype system has been developed, which is able to demonstrate some emergent human social behaviors.

TL;DR: This paper developed a system that analyzes the sentences contained in unstructured or semi-structured documents, and utilizes an ontology reflecting the domain knowledge for a semantic classification of the documents.