Dr Ron Grau
|Post:||Visiting Research Fellow (Informatics)|
|Location:||Chichester 1 Ci207|
|download vCarddownload vCard to your mobile|
I am a Visiting Research Fellow in the School of Informatics.
I am interested in the modeling and discovery of knowledge in complex real-world domains, and specifically in the development of computational tools that employ diagrammatic representation systems to support these tasks.
Diagrams have been shown to be capable of encoding and formalizing the conceptual dimensions underlying many complex problems, and can be designed to incorporate the multiple abstractions, paradigms and perspectives of the related knowledge. When combined with other forms of representation and embedded into novel, interactive knowledge-based tools, diagrammatic representations may support research and scientific discovery in domains that present problems which are currently difficult to approach with the sole use of quantitative methods.
In my thesis, I dealt with the acquisition and representation of expert knowledge in domains with complex multi-dynamic (CMD) processes, an ill-structured problem which involves rich amounts of heterogeneous knowledge. The research was applied to industrial bakery product manufacturing. This is a challenging real-world domain which comprises a variety of physical, chemical and bio-chemical process combinations. An integrative framework of knowledge representations and acquisition methods has been developed and implemented in the software prototype CMD SUITE. The framework takes a compositional, collaborative approach to knowledge acquisition by providing methods for the decomposition of different processes into process fragments and the localization of structural change, behavior and function within the fragments and the system of processes. Diagrams presented an important part of the framework, as they provide a range of representational, cognitive and computational properties that are useful for meeting many of the challenges that CMD processes pose.
Bar-Yam, Y.: Dynamics of Complex Systems. Perseus Books, Cambridge, MA. (1997)
Bechtel, W. and R. C. Richardson: Discovering complexity: decomposition and localization as strategies in scientific research. (1993)
Burns, C. M., & Hajdukiewicz, J. R.: Ecological interface design. Boca Raton: CRC Press (2004)
Cheng, P. C.-H., & Barone, R.: Representing complex problems: A representational epistemic approach. In D. H. Jonassen (Ed.), Learning to solve complex scientific problems (pp. 97-130). Mahmah, N.J.: Lawrence Erlbaum (2007)
Cheng, P. C.-H., & Simon, H. A.: Scientific discovery and creative reasoning with diagrams. In S. Smith, T. Ward & R. Finke (Eds.), The Creative Cognition Approach (pp. 205-228). Cambridge, MA: MIT Press (1995)
Iwasaki, Y. Reasoning with Multiple Abstraction Models. In: Boi Faltings, Peter Struss (eds .): Recent Advances in Qualitative Physics, MIT Press (1992)
Klahr, D., & Dunbar, K.: Dual space search during scientific reasoning. Cognitive Science. 12, 1-48 (1988)
Larkin, J.H., Simon, H.A.: Why a Diagram is (Sometimes) Worth Ten Thousand Words. Cognitive Science Vol. 11, Issue 1, 65-100. (1987)
Kulkarni, D., & Simon, H.A.: The processes of scientific discovery: The strategy of experimentation. Cognitive Science, 12, 139-176 (1988)
Langley, P.: Lessons for the computational discovery of scientific knowledge. Proc. of First Int. Workshop on Data Mining Lessons Learned. Sydney (2002)
Shrager, J.: Tools for thought in the age of biological knowledge, Workshop on Quantitative Education in Biological Science, University of Maryland, Baltimore Campus. (2004)
Simon, H.A.: The architecture of complexity. Proc. of the American Philosophical Society, 106, 467-482 (1962)
Simon, H.A.: The structure of ill-structured problems. Artificial Intelligence, no. 4, pp. 181-202. (1973)
Grau, Ron (2009) The Acquisition and Representation of Knowledge about Complex Multi- Dynamic Processes. University of Sussex.