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Date: Fri, 21 Jul 95 19:05:15 EDT
From: AI.Repository@GLINDA.OZ.CS.CMU.EDU
To: ai+ai-postdoc@cs.cmu.edu, ai+ai-predoc@cs.cmu.edu
Subject: Predoc: Fuzzy AI at Univ. of Bristol (UK)
Sender: ai@A.GP.CS.CMU.EDU
From: entpm@zeus.bris.ac.uk (TP. Martin)
Subject: Research Opportunity (University of Bristol)
Date: Fri, 7 Jul 1995 10:40:04 GMT
Research Opportunities in Fuzzy Artificial Intelligence
The Artificial Intelligence group at the University of Bristol (headed
by Professor J.F. Baldwin) has a vacancy for a postdoctoral research
assistant and a postgraduate research student to work on the topics
described below.
1. PhD Case Studentship in Knowledge Engineering
A student with a good honours degree in Mathematics, Physics, Computer
Science or Engineering is required to work on the development of a
fuzzy intelligent data browser for obtaining knowledge from large
volume data. This work will be done in co-operation with DRA, Mavern.
Starting date is October 1995.
We live in the age of information - large amounts of data for a wide
range of subject matter is there for the collecting - but data is
numbers and intelligence is needed to make sense of it and convert it
into worthwhile knowledge. Scientists, engineers, managers, business
decision makers from many disciplines collect large amounts of data to
be used to determine models for their applications. The data can
represent pictures and graphics, sound, numbers and text. To know
something is to understand the relationship between parts or features
or concepts, to relate to a context, to obtain models, to use to infer.
To discover is to find these relationships, to hypothesise and to
justify. The models may be in mathematical form as equations, in logic
form as propositions, in linguistic form as natural language
statements, probabilistic in nature and use fuzzy representations.
These models provide a summarisation of the data - a high level form of
data compression.
A data browser can answer queries with reference to a large database. The
database can contain uncertain, vague and fuzzy attribute values. To
answer a query some form of interpolation between near matching
appropriate entries in the database may be required. This interpolation
can take the form of forming fuzzy, probabilistic, mixed fuzzy
probabilistic rules from the relevant data base entries. The browser
effectively and intelligently fills in for missing information,
constructs partial matchings and uses these to answer the query using a
form of case based reasoning.
The browser will be useful for many applications such as data mining,
pattern recognition, fuzzy control, databases containing uncertainties
etc. and financial modelling.
2. A Post-Doctoral Research Assistant
is required to work on an EPSRC funded project
"Mathematical Modelling and Knowledge Engineering for Engineering Design"
Candidates should have experience with some of the following:
- knowledge based systems
- logic programming
- mathematical modelling
- uncertainty in AI
- Mathematica
- user friendly interfaces.
This project is concerned with the development of a software
environment for intelligent engineering analysis and design. The
integration of mathematical models with logic-style knowledge bases
should provide an intelligent working environment for the Engineer to
use as a software laboratory in conjunction with the hardware
laboratory for design purposes.
This is not a simple concatenation of mathematics software with
artificial intelligence software but represents an integration in which
the mathematics aids the intelligence of the AI software and the
artificial intelligence aids the validity of the mathematics software.
The Engineer uses mathematical models, CAD software, intuition based on
experience, simplifications and approximations, assumptions and design
creativity when designing a new product. At present the Engineer uses
NAG routines to perform numerical calculations for evaluating the
mathematical model, graphics packages to see the results and
specialised CAD software to help with the design. The Engineer is
responsible for determining which models and assumptions are applicable
to answer a given question, for providing explanations of why a
certain result occurred, for setting up new conditions, assumptions,
models and links with software packages to answer "what if" questions.
This is in addition to the creativity expected in constructing the
necessary changes in design for the next iteration of the iterative
design process. The Engineer is expected to memorise relevant
information or know how to find it.
Two software systems exist today which the Engineer should learn to
exploit far more intelligently than has been done to date. These are
the mathematical symbol manipulating program Mathematica and the
Artificial Intelligence language FRIL. Each by itself provides a
powerful computing tool for the engineer but each one also has missing
elements. Taken together, with one being able to ask questions of the
other and data able to pass freely from one to the other, the
combination will provide a powerful intelligent design environment.
Supervision
The research will be supervised by
Prof J.F. Baldwin, Professor of Artificial Intelligence, EPSRC Senior Research F
ellow
and Dr. T.P. Martin
Further Information:
http://www.fen.bris.ac.uk/engmaths/research/aigroup/resopps.html
or contact
Jim.Baldwin@bristol.ac.uk
Trevor.Martin@bristol.ac.uk
_______________________________________________________________________________ Advanced Computing Research Centre || Phone: +44 117 9288200
Department of Engineering Maths || Fax: +44 117 9251154
University of Bristol, BS8 1TR, UK || email: trevor.martin@bris.ac.uk_______________________________________________________________________________
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