The human ability to process images and understand what they mean in order to solve a problem holds an important clue to how the human thought process works. This suggests a representation which orientates itself on the perception of the world. But, is such a representation also suitable for modeling problem solving, a domain which is traditionally reserved for the symbolic approach? An important research field in artificial intelligence is the usage of heuristics to speed up the search. It is not easy to define heuristic functions, as there is no rule which says how to do this. Another approach to the view of heuristic functions is shown in this work: heuristic functions which result from the manner of description of knowledge, namely by perception orientated representation. Examples of such representation are two dimensional binary sketches, or numbers represented by bars at certain positions which can overlap. Experiments with a neural production system with this kind of representation are performed in the 8-puzzle and the block world domain.
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