The Second International Workshop on Spatio-Temporal Reasoning and Learning (STRL 2023), collocated with IJCAI 2023 (https://ijcai-23.org/)

Website: https://codesign-lab.org/strl23/ (under construction)


Introduction
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Opposing the false dilemma of logical reasoning vs machine learning, we argue for a synergy between these two paradigms in order to obtain hybrid, human-centred AI systems that will be robust, generalisable, explainable, and ecologically valid. Indeed, it is well-known that machine learning only includes statistical information and, therefore, on its own is inherently unable to capture perturbations (interventions or changes in the environment), or perform explainable 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 available a priori. It is becoming ever more evident in the literature that modular AI architectures should be prioritised, 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.

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 formal methods developed within the spatial and temporal reasoning community, be it qualitative or quantitative, naturally build upon (commonsense) physics and human cognition, and could therefore form a module that would be beneficial towards causal representation learning. A (relational) spatio-temporal knowledge base could provide a foundation upon which machine learning models could generalise, and exploring this direction from various perspectives is the main theme of this workshop.


Topics
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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:

-Neuro-symbolic approaches for spatio-temporal reasoning and learning
-Declarative spatial reasoning
-(Commonsense) Reasoning about space, actions, and change
-Spatial and temporal language understanding with and without additional modalities (e.g., vision)
-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

Application domains being addressed include, but are not limited to:

-Autonomous Driving
-Cognitive Robotics
-Spatial Computing for Design
-Computational Art
-Cognitive Vision
-Geographic Information Systems


Submission
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Guidelines
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Papers should be formatted according to the CEUR-ART style formatting guidelines (available at the workshop website) 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 poster, and submissions that are at least 5 pages and up to 7 pages long (again, excluding references and appendices) will be considered for an oral 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). Workshop submissions will be handled by EasyChair; the submission link is as follows: https://easychair.org/conferences/?conf=strl2023


Important Dates
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May 12, 2023: Paper submission deadline

May 31, 2023: Paper notification

June 7, 2023: Camera-ready submission deadline

June 15, 2023: Early registration deadline

August 19-20, 2023: Workshop date (exact date to be announced)

Note: all deadlines are AoE (Anywhere on Earth).


Proceedings
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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 2023 is a workshop, not a conference, submission of the same paper to conferences or journals is acceptable from our standpoint.


Organizing Committee
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Dr. Michael Sioutis, LIRMM UMR 5506, University of Montpellier, CNRS, France

Dr. Zhiguo Long, Southwest Jiaotong University, Chengdu, China

Dr. Jae Hee Lee, University of Hamburg, Germany

Prof. Mehul Bhatt, Örebro University, Sweden - CoDesign Lab EU


Contact
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All questions about submissions should be emailed to strl2023 at easychair.org