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Commonsense, Space, Change

The integration of spatial representation and reasoning techniques within general commonsense reasoning frameworks in AI is an essential next-step for their applicability, e.g., in the form of spatial control and spatial planning in cognitive robotics, for spatial decision-support in intelligent systems, e.g., design assistance, wayfinding and navigation assistance, and as explanatory models in a wide-range of systems requiring the formulation of hypotheses, e.g., spatio-temporal diagnosis and abnormality detection, event recognition and behaviour interpretation, geospatial dynamics and event-based geographic information systems.

More generally, the key challenge is to broaden the initial interpretation of `spatial reasoning' to include classical and non-classical inference patterns, as they accrue within a spatial, spatio-temporal, action and change, ontological, and commonsense reasoning context.

Specialisation and Integration

If `spatial reasoning', both qualitative and otherwise, and commonsense notions of space and spatial change are to be embedded or utilized within practical or larger application scenarios in AI, their integration with formal AI languages, calculi, and tools to model change and high-level inference patterns need to be thoroughly investigated, i.e., from ontological, representational and computational viewpoints. Furthermore, it is necessary that the integration and the supported computational mechanisms be generic / applicable in a wide-range of application domains, very much like generic knowledge representation languages and frameworks themselves.

Space, Actions, and Change

Space and time are inextricably linked, i.e., spatial configurations change over time. Humans, robots and systems that act, and interact, are embedded in space, and this change is often the result of actions and events. Actions and events are a critical link to the external world, in a predictive as well as an explanatory sense: our anticipations of spatial reality conform to our commonsense knowledge of the effects of actions and events in the real world. Similarly, explanations of the perceived reality (e.g., by humans, robots, systems) also are established on the basis of such apriori commonsense notions.

Spatial and Temporal Reasoning

The field of qualitative spatial representation and reasoning has evolved as a sub-division in its own right within the broader field of Artificial Intelligence -- recent years have witnessed remarkable advances in some of the long-standing problems of the field. For instance, new results about tractability for spatial calculi, explicit construction of models, characterisation of important subclasses of relations, as well as in the development of new areas such as the emergence of integrated spatio-temporal calculi and the importing of non-monotonic techniques for dealing with various aspects intrinsic to dynamic spatial systems. Inextricably linked to space is time, i.e., spatial configurations change over time. Spatial change may also be perceived as being spatio-temporal and recent work has been devoted to providing useful and well-grounded models to be used as high level qualitative description of spatio-temporal change. Reasoning about space and spatial dynamics also involves reasoning about changing spatial configurations, and in more realistic scenarios, integrated reasoning about space, actions and change. Recent work supporting this paradigm has also explicitly addressed the formal modelling of dynamic spatial systems and ensuing interactions between the spatial reasoning domain and the field of reasoning about actions and change, and commonsense reasoning.

Driven by cognitive approaches that characterise the processing of spatial information within qualitative spatial reasoning, there has been considerable influx of people from other areas within AI such as computer vision, robotics etc, working on qualitative representation and reasoning about spatial change, spatio-temporal interactions, and the formal modelling of dynamic spatial systems in general. Qualitative conceptualisations of space and tools/techniques for efficiently reasoning with them being well-established, there is now a clear felt need within the community to utilise the tools and formalisms that have been constructed in the recent years in novel application scenarios.
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