| Vol-3827 urn:nbn:de:0074-3827-4 Copyright © 2024 for the individual papers by the papers' authors. Copyright © 2024 for the volume as a collection by its editors. This volume and its papers are published under the Creative Commons License Attribution 4.0 International (CC BY 4.0).

# STRL 2024
Spatio-Temporal Reasoning and Learning 2024

### Proceedings of the 3rd International Workshop on Spatio-Temporal Reasoning and Learning (STRL 2024)
co-located with the 33rd International Joint Conference on Artificial Intelligence (IJCAI 2024)

### Jeju island, South Korea, August 5, 2024.

Edited by

### Parisa Kordjamshidi *
Jae Hee Lee **
Mehul Bhatt ***
Michael Sioutis ****
Zhiguo Long *****

* Michigan State University, Department of Computer Science and Engineering, USA
** University of Hamburg, Department of Informatics, Hamburg, Germany
*** Örebro University, School of Science and Technology, Örebro, Sweden
**** University of Montpellier, Laboratory of Computer Science, Robotics and Microelectronics of Montpellier, France
***** Southwest Jiaotong University, School of Computing and Artificial Intelligence, Chengdu, China

## Table of Contents

- Preface
  Summary: There were 9 papers submitted for peer-review to this workshop. Out of these, 7 papers were accepted for this volume, 6 as regular papers and 1 as short paper. Finally, the proceedings were supplemented with 2 keynotes and 2 invited papers.

### Keynotes

- Some Connections between Qualitative Spatial Reasoning and Machine Learning (Abstract)
  Anthony G Cohn
- Applications of Spatial and Temporal Reasoning in Cognitive Robotics (Abstract)
  Esra Erdem

### Peer-reviewed Papers

- A Spatial Loss Function for Gradient Boosted Trees
  Margot Geerts, Seppe vanden Broucke, Jochen De Weerdt
- A spatiotemporal graph neural network with multi granularity for air quality prediction
  Haibin Liao, Li Yuan, Mou Wu
- Encoding Temporal Statistical-space Priors via Augmented Representation under Data Scarcity
  Insu Choi, Woosung Koh, Gimin Kang, Yuntae Jang, Woo Chang Kim
- Improving Accuracy of Anomaly Detection in Spatial-Temporal Population Data through SHAP Values of Reconstruction Errors
  Ryo Koyama, Tomohiro Mimura, Shin Ishiguro, Keisuke Kiritoshi, Takashi Suzuki, Akira Yamada
- ConvLSTM Neural Network based on Hexagonal Inputs for Spatio-Temporal Forecasting of Traffic Velocities
  Francisco Bahamondes, Billy Peralta, Orietta Nicolis, Andres Bronfman, Alvaro Soto
- SpoT-Mamba: Learning Long-Range Dependency on Spatio-Temporal Graphs with Selective State Spaces
  Jinhyeok Choi, Heehyeon Kim, Minhyeong An, Joyce Jiyoung Whang
- GESA: A GEneral Scenario-Agnostic Reinforcement Learning for Traffic Signal Control
  Haoyuan Jiang, Ziyue Li, Zhishuai Li, Lei Bai, Hangyu Mao, Wolfgang Ketter, Rui Zhao

### Invited Papers

- Neuro-symbolic Tuning for Multi-hop Reasoning over Spatial Language (Invited Paper)
  Tanawan Premsri, Parisa Kordjamshidi
- Neurosymbolic Visual Commonsense: On Integrated Reasoning and Learning about Space and Motion in Embodied Multimodal Interaction (Invited Paper)
  Mehul Bhatt

2024-11-08: submitted by Michael Sioutis, metadata incl. bibliographic data published under Creative Commons CC0
2024-11-11: published on CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073) |valid HTML5|