论文
International Journal of Geographical Information Science
PublisherJournal
GeoAI
中文标题
利用图逆强化学习生成不完整数据下的地理空间轨迹
English Title
Generating geospatial trajectories with incomplete data using graph inverse reinforcement learning
Zi Hen Lin A. Yair Grinberger Daniel Felsenstein a Department of Computer Science, Technical University of Munich, Germanyb Department of Geography, The Hebrew University of Jerusalem, IsraelZi Hen Lin is a Doctoral Researcher in Informatics at the Technical University of Munich. His work focuses on machine learning for simulations, scientific computing, and infectious disease prediction, especially in relation to COVID-19 agent-based models and urban diffusion.A. Yair Grinberger is a Senior Lecturer in the Department of Geography at the Hebrew University of Jerusalem. His fields of interest are GIScience, volunteered geographic information, mobility analysis, urban modeling, and the extraction of cultural knowledge from geodata.Daniel Felsenstein is a Professor of Geography at the Hebrew University of Jerusalem. His research focuses on economic geography, regional science, spatial econometrics, simulation modeling, urban resilience, housing markets, and developing a spatial general equilibrium model for Israel.
发布时间
2026/4/27 20:46:18
来源类型
journal
语言
en
摘要
Geographic simulations of human systems often rely on trajectory generation to model agent behavior. This paper addresses trajectory generation under conditions of limited data. We demonstrate how ...
元数据
来源International Journal of Geographical Information Science
类型论文
抽取状态raw
关键词
PublisherJournal
GeoAI