Details of Grant 

EPSRC Reference:	EP/E011969/1
Title:	Workshop on Soft Methods in Probability and Statistics
Principal Investigator:	Lawry, Professor J
Other Investigators:	Martin, Professor T Flach, Professor P
Researcher Co-Investigators:
Project Partners:
Department:	Engineering Mathematics
Organisation:	University of Bristol
Scheme:	Standard Research
Starts:	01 September 2006	Ends:	30 November 2006	Value (£):	7,247
EPSRC Research Topic Classifications:	Artificial Intelligence Statistics & Appl. Probability
EPSRC Industrial Sector Classifications:	No relevance to Underpinning Sectors
Related Grants:
Panel History:
Summary on Grant Application Form
The SMPS 2006 workshop will provide a forum for research and discussion into the fusion of soft methods with probability and statistics, with the ultimate goal of integrated uncertainty modelling in complex systems involving human factors. In addition to probabilistic factors such as measurement error and other random effects, the modelling process often requires us to make qualitative and subject judgements that cannot easily be translated into precise probability values. Such judgements give rise to a number of different types of uncertainty including; fuzziness if they are based on linguistic information; epistemic uncertainty when their reliability is in question; ignorance when they are insufficient to identify or restrict key modelling parameters; imprecision when parameters and probability distributions can only be estimated within certain bounds. Statistical theory has not traditionally been concerned with modelling uncertainty arising in this manner but soft methods, a range of powerful techniques developed within AI, attempt to address those problems where the encoding of subjective information is unavoidable. These are mathematically sound uncertainty modelling methodologies which are complementary to conventional statistics and probability theory. Therefore, a more realistic modelling process providing decision makers with an accurate reflection of the true current state of our knowledge (and ignorance) requires an integrated framework incorporating both probability theory, statistics and soft methods. This fusion motivates innovative research at the interface between computer science (AI), mathematics and systems engineering. NOTE: In view of the fact that soft methods form part of the AI research area we feel that it would be most appropriate if this proposal were initially considered by the ICT panel
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Organisation Website:	http://www.bris.ac.uk