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Research Areas

With respect to its basic Research Topics, the contemporary scientific agenda of STeDy addresses several areas within Knowledge Representation and Reasoning (KR) in particular, and reaches out to all sub-disciplines within Artificial Intelligence, Spatial Cognition, and Cognitive Technologies in general. Some core KR areas being addressed include:
  • Spatial Representation and Reasoning
  • Commonsense Reasoning
  • Qualitative Reasoning
  • Reasoning about Actions and Change
  • Logic-based Modelling of Dynamic Systems
  • Language, Ontology, and Space
  • Spatial Learning
  • Cognitive Technologies and Spatial Cognition
  • Other areas of AI where Space, Time, Events, Actions, Change, Causality, Dynamics, Spatio-Temporal Learning play an important role are welcome to contribute to all initiatives within STeDy. If in doubt, please do not hesitate to directly email the responsible contact person(s).

    Topics of Interest

    Main topics of interest include:
  • Representing and reasoning about dynamic spatial systems
  • Non-monotonic reasoning in dynamic spatial systems
  • Abduction for spatial knowledge discovery
  • Spatio-Temporal Abduction, Causal explanation with spatio-temporal data
  • Declarative spatial representation and reasoning, with:
    • Logic Programming, Abductive Logic Programming
    • Constraint Logic Programming
    • Answer-Set Programming
  • Qualitative reasoning
  • Qualitative spatial representation and reasoning
  • Qualitative spatio-temporal continuity
  • Visual and diagrammatic reasoning
  • Spatio-Temporal belief revision
  • Non-Monotonic causal formalizations of spatio-temporal change
  • Spatial and physical reasoning
  • Concurrency in the spatial domain
  • Integrated approaches for modelling and reasoning about space, actions and change
  • Event-based Modelling
  • Spatio-Temporal Narratives
  • Spatio-Temporal Query Languages
  • Commonsense ontologies of spatio-temporal dynamics
  • Integrated spatial and ontological reasoning
  • Ontologies for spatial scene descriptions (e.g., indoor environments, room-space)
  • Grounding processes for perceptual environmental data with spatial ontologies
  • Space, Motion, Natural Language
  • Mapping of NL to spatial representation and reasoning
  • Geometric Space, Mereology, Mereogeometry
  • Shape and 3D space
  • Commonsense and Qualitative models of visibility
  • Qualitative abstractions of motion (e.g., for robotics, events and processes in geospatial dynamics)
  • Learning of commonsensical, qualitative spatial representations
  • Hybrid qualitative-qualitative reasoning
  • Qualitative abstractions for Machine Learning
  • Planning, explanation, simulation, and learning within dynamic spatial systems
  • Application Areas

    Some applications areas of special interest that have also witnessed recent attention include:
  • Spatial Computing for Design (e.g., diagnosis, requirement consistency)
  • Cognitive Robotics (e.g., high-level spatial planning & control)
  • Geospatial Dynamics (e.g., reasoning with events and processes in GIS)
  • Behaviour and Activity Interpretation
  • Ambient Intelligence and Smart Environments
  • Computer-Aided Learning (CAL) (e.g., question-answering, NLU applications)
  • Computer-Aided Design (CAD)
  • Sketch Recognition and Understanding
  • Location-based Services
  • Real-time Systems (e.g., traffic, transportation)
  • Assistive technologies dealing with spatio-temporal Information
  • Commonsense notions of space & change in biology, physics, and chemistry
  • Hybrid Intelligent Sytems with a Spatial, Temporal or Spatio-Temporal component
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