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AAAI 2010 Spring Symposium "Cognitive Shape Processing"

In the recent decades there has been a growing interest in understanding and computationally investigating how spatial information is processed in natural intelligent sys tems. The inter disci plinary field of spatial cognition, besides its basic research related motivation, also aims at improving artificial systems by transferring natural principles to technical systems, e.g. in ro botics, in intelligent instruction systems or in other intelligent interactive systems.

In spatial cognition, numerous aspects of spatial knowledge are investigated, among these spatial reference systems, topological information, route knowledge, knowledge about distances and directions, etc. For all these aspects, specific forms of representation and formalisms for reasoning about them have been devised. Common to most of the formalisms is that they usually deal with spatial knowledge on a high level of abstraction. In some cases the formalisms only consider some knowledge aspects in isolation (e.g., orientation knowledge), and in other cases they only deal with highly simplified spatial objects such as points or basic geometric forms.

In contrast to this abstraction, real-world problems typically deal with diverse types of spatial knowledge at the same time and involve complex objects with meaningful and specific shapes. Understanding mental processing of knowledge about shapes thus seems essential for under standing mental processing of spatial knowledge in real world scenarios. Importantly, addressing shape knowledge also offers the potential of integrating diverse aspects of spatial knowledge processing since all types of spatial knowledge are affected by shape. So, on the one hand, shape is a specific type of spatial knowledge (among others), on the other hand shape processing involves the most challenging aspect of spatial knowledge processing since it cannot be dealt with in an abstract manner and it affects all other forms of spatial knowledge.

With the term Cognitive Shape Processing we refer to all forms of knowledge processing in volving shape information that are related to, inspired by, or derived from principles found in natural cognitive systems. We thus exclude purely technical approaches to shape processing, however we strongly encourage considering cognitive principles as potential solutions for technical approaches. Unfortunately, and contrary to many other visuo-spatial aspects of cog­nition, cognitive shape processing has not yet received the appropriate level of attention in the scientific community. Considering the potentials of understanding and employing the principles of cognitive shape processing for both basic and applied research, this clearly calls for a joint endeavor in AI and the cognitive sciences to sufficiently address its most fundamental questions.

Date: March, 22 - 24, 2010

Location: Stanford University, USA

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