Instruct: Given the title of a scientific paper, retrieve paper titles that are cited by the given paper.
Query: Spatiotemporal simulation of urban growth patterns using agent-based modeling: The case of Tehran
Integration of logistic regression, Markov chain and cellular automata models to simulate urban expansion
Dynamics of Urbanization and Its Impact on Land-Use/Land-Cover: A Case Study of Megacity Delhi
Agent-based modeling: Methods and techniques for simulating human systems
Connected Population Synthesis for Urban Simulation
Evaluation of urban sprawl and urban landscape pattern in a rapidly developing region
Making Models Match: Replicating an Agent-Based Model
Spatio-Temporal Patterns and Policy Implications of Urban Land Expansion in Metropolitan Areas: A Case Study of Wuhan Urban Agglomeration, Central China
gis - based urban modelling : practices , problem , and prospects .
A Computer Movie Simulating Urban Growth in the Detroit Region
Simulating crowd movement in agent-based model of large-scale flood
Tutorial on Agent-Based Modeling and Simulation PART 2: How to Model with Agents
A tale of many cities: universal patterns in human urban mobility
Human mobility modeling at metropolitan scales
SUNtool – A new modelling paradigm for simulating and optimising urban sustainability
Procedural modeling of cities
Measurement and monitoring of urban sprawl in a rapidly growing region using entropy
Multi-city sustainable regional urban growth simulation—MSRUGS: a case study along the mid-section of Silk Road of China
How congestion shapes cities: from mobility patterns to scaling
Introductory tutorial: agent-based modeling and simulation
Agent-based modeling and simulation
Social Comparison as a Predictor of Body Dissatisfaction: A Meta-Analytic Review
Design and development of wireless sensor node for anti-poaching
A Self-Modifying Cellular Automaton Model of Historical Urbanization in the San Francisco Bay Area
Detection and Discrimination of Open-Phase Fault in Permanent Magnet Synchronous Motor Drive System
Feature Control as Intrinsic Motivation for Hierarchical Reinforcement Learning