Date : 2024-08-05
Lieu : Co-localisé avec la conférence IJCAI 2024, île de Jeju, Corée du Sud
Call For Papers
The 3rd International Workshop on Spatio-Temporal Reasoning and Learning (STRL 2024) will take place in Jeju, South Korea, collocated with IJCAI 2024.
Website: https://www.lirmm.fr/strl2024/
Introduction
Opposing the false dilemma of logical reasoning vs machine learning, we argue for a synergy between these two paradigms in order to obtain hybrid AI systems that will be robust, generalizable, and transferable.
Indeed, it is well-known that machine learning only includes statistical information and, therefore, is not inherently able to capture perturbations (interventions or changes in the environment), or perform reasoning and planning. Ideally, (the training of) machine learning models should be tied to assumptions that align with physics and human cognition to allow for these models to be re-used and re-purposed in novel scenarios.
On the other hand, it is also the case that logic in itself can be brittle too, and logic further assumes that the symbols with which it can reason are already given.
It is becoming ever more evident in the literature that modular AI architectures should be prioritized, where the involved knowledge about the world and the reality that we are operating in is decomposed into independent and recomposable pieces, as such an approach should only increase the chances that these systems behave in a causally sound manner.
You may find details about previous editions of this workshop via the links below:
The aim of this workshop is to formalize such a synergy between logical reasoning and machine learning that will be grounded on spatial and temporal knowledge.
We argue that the calculi associated with the spatial and temporal reasoning community, be it qualitative or quantitative, naturally build upon physics and human cognition, and could therefore form a module that would be beneficial towards causal representation learning. A (symbolic) spatio-temporal knowledge base could provide a dependable causal seed upon which machine learning models could generalize, and exploring this direction from various perspectives is the main theme here.
Topics
In this workshop, we invite the research community in artificial intelligence to submit works related to the proposed integration of spatial and temporal reasoning with machine learning, revolving around the following topic areas:
- Real-world problems / applications involving spatio-temporal data
- Spatial, temporal, and spatio-temporal knowledge graphs
- Spatio-temporal data mining / analysis
- Space and time in narratives
- Declarative spatial reasoning
- Spatial and temporal language understanding with and without additional modalities (e.g., vision)
- Neuro-symbolic approaches for spatio-temporal reasoning and learning
- Probabilistic world models for spatio-temporal reasoning and learning
- Probabilistic inference for spatio-temporal reasoning and learning
- Datasets for spatio-temporal reasoning and learning
- Metrics for assessing spatio-temporal reasoning and learning methods
- Limitations in machine learning for spatio-temporal reasoning and learning; how far can machine learning go?
- Relation between causal reasoning and spatial and temporal reasoning
- Research and teaching challenges in spatio-temporal reasoning and learning
The list above is by no means exhaustive, as the aim is to foster the debate around all aspects of the suggested integration.
Application domains being addressed include, but are not limited to:
- Autonomous Vehicles and Drones
- Cognitive Robotics
- Spatial Computing for Design
- Computational Art
- (Cognitive) Vision
- Geographic Information Systems
- Smart Environments
- Healthcare
Submission
The submission link is available at: https://easychair.org/conferences/?conf=strl2024
Papers should be formatted according to the CEUR-ART style formatting guidelines here and submitted as a single PDF file.
We welcome submissions across the full spectrum of theoretical and practical work including research ideas, methods, tools, simulations, applications or demos, practical evaluations, and surveys.
Submissions that are 2 pages long (excluding references and appendices) will be considered for a short presentation, and submissions that are between 4 and 7 pages long (again, excluding references and appendices) will be considered for a regular presentation.
All papers will be peer-reviewed in a single-blind process and assessed based on their novelty, technical quality, potential impact, clarity, and reproducibility (when applicable).
Be mindful of the following dates:
- April 26, 2024: Workshop paper submission deadline
- May 31, 2024: Paper acceptance/rejection notification date
- June 7, 2024: Camera-ready submission deadline
- August 5, 2024: Workshop Date
Note: all deadlines are AoE (Anywhere on Earth).
Proceedings
The accepted papers will appear on the workshop website. We also intend to publish the workshop proceedings with CEUR-WS.org; this option will be discussed with the authors of accepted papers and is subject to the CEUR-WS.org preconditions. We note that, as STRL 2024 is a workshop, not a conference, submission of the same paper to conferences or journals is acceptable from our standpoint.
Workshop Organizers
- Parisa Kordjamshidi, Michigan State University, US (co-chair) https://www.cse.msu.edu/~kordjams/
- Jae Hee Lee, University of Hamburg, Germany (co-chair) https://jaeheelee.gitlab.io/
- Mehul Bhatt, Örebro University, Sweden (co-chair) https://mehulbhatt.org/
- Michael Sioutis, University of Montpellier, France (co-chair) https://msioutis.gitlab.io/
- Zhiguo Long, Southwest Jiaotong University, Chengdu, China (co-chair) https://zhiguolong.github.io/
Notre site web : www.madics.fr
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