Title :
A strategy of knowledge representation for uncertain problems: modeling domain expert knowledge with patterns
Author_Institution :
Comput. & Autom. Res. Inst., Hungarian Acad. of Sci., Budapest, Hungary
fDate :
10/1/1995 12:00:00 AM
Abstract :
Patterns as sets of somehow coherent information are feasible metaphors and tools for representation of weakly structured or unstructured knowledge in an open, infinite world. This view follows the evolutionary theory of mind representation. A practical computational formulation is given with pattern relationships based on the metapattern concept. The pattern space is mostly nonmetric due to the limited dimensional view of infinite dimensional objects. The faults of the metric suggest directions in exploring further knowledge and eliciting tacit knowledge of experts. Man-machine interaction has a special role in the process, explored by cognitive psychology methods and special graphic tools for input-output representation
Keywords :
knowledge acquisition; knowledge representation; man-machine systems; cognitive psychology methods; domain expert knowledge modelling; evolutionary theory; graphic tools; infinite dimensional objects; input-output representation; knowledge representation strategy; man-machine interaction; metapattern concept; mind representation; open infinite world; pattern relationships; tacit knowledge elicitation; uncertain problems; unstructured knowledge; weakly structured knowledge; Automation; Cognitive science; Dictionaries; Graphics; Humans; Knowledge representation; Machine learning; Man machine systems; Pattern recognition; Psychology;
Journal_Title :
Systems, Man and Cybernetics, IEEE Transactions on
Conference_Location :
10/1/1995 12:00:00 AM