The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford University's Department of Computer Science, is pleased to present the 2010 Spring Symposium Series, to be held Monday through Wednesday, March 22–24, 2010 at Stanford University. The titles of the seven symposia are Artificial Intelligence for Development; Cognitive Shape Processing; Educational Robotics and Beyond: Design and Evaluation; Embedded Reasoning: Intelligence in Embedded Systems Intelligent Information Privacy Management; It's All in the Timing: Representing and Reasoning about Time in Interactive Behavior; and Linked Data Meets Artificial Intelligence.

The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford University’s Department of Computer Science, is pleased to present the 2010 Spring Symposium Series, to be held Monday through Wednesday, March 22–24, 2010 at Stanford University. The titles of the seven symposia are Artificial Intelligence for Development; Cognitive Shape Processing; Educational Robotics and Beyond: Design and Evaluation; Embedded Reasoning: Intelligence in Embedded Systems Intelligent Information Privacy Management; It’s All in the Timing: Representing and Reasoning about Time in Interactive Behavior; and Linked Data Meets Artificial Intelligence.

A sizable fraction of current research into human visuo-spatial knowledge processing explicitly or implicitly suggests a spatial processing of certain knowledge types and a visual processing of others. Similarly, many formal and technical approaches for representing and processing visuo-spatial information in artificial intelligence, in computational cognitive modeling, or in knowledge representation and reasoning explicitly or implicitly treat visual and spatial information as belonging to separate types. While there exists good evidence for some differences in mental processing of different visuo-spatial knowledge types, there is much less reason to maintain the currently ascribed separation between the visual and the spatial. We provide arguments on why strict dichotomies seem unwarranted with regard to descriptions of human mental spatial reasoning and disadvantageous for the formal and technical approaches. We build upon a synopsis of psychological evidence for the existence of multiple knowledge type specific representations in human visuo-spatial reasoning and discuss the notion of scalable representation structures. In absence of proof to the contrary, it seems better practice to assume that (a) many of the type differences attributed to visuo-spatial knowledge processing are gradual rather than qualitative in nature, and that (b) tasks involving visuo-spatial knowledge of several types are often mentally processed through dynamic associations of structures for processing basal knowledge types. The paper calls for more investigations of human reasoning in visuo-spatial tasks in which knowledge types dynamically change during reasoning. It outlines a research framework for systematically investigating different basal visuo-spatial knowledge types and their combinations with regard to cognitive and computational plausibility. Current research is related to the framework, including research on Casimir, our computational cognitive architecture for reasoning with visuo-spatial knowledge. We argue that a more systematic course of research along the lines of the proposed framework will not only lead to more appropriate descriptions of human cognition (regarding visuo-spatial knowledge processing) but may also spawn more integrated and versatile formal and technical approaches for dealing with visuo-spatial information.