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NL-KR Digest Volume 13 No. 22
NL-KR Digest Sun May 29 23:50:28 PDT 1994 Volume 13 No. 22
Today's Topics:
CFP: AI'94 7th Australian Joint Conf. on AI, Nov 94, Armidale
CFP: AI'94 TUTORIAL ON INTELLIGENT LEARNING DATABASE SYSTEMS
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-----------------------------------------------------------------------
Date: Wed, 18 May 1994 04:42:54 -0700
Reply-To: ai94@fermat.une.edu.au
From: Artificial Intelligence Conference 1994 <ai94@fermat.une.edu.au>
To: al
Subject: CFP: AI'94 7th Australian Joint Conf. on AI, Nov 94, Armidale
T H I R D C A L L F O R P A P E R S
Seventh Australian Joint Conference on Artificial Intelligence (AI'94)
"Sowing the Seeds for the Future"
21 - 25 November 1994
Proudly sponsored by
Microsoft Institute (principal sponsor),
IBM, Sun Microsystems, Australian Computer Society, CAMTECH Pty. Ltd.,
Knowledge Engineering Group - Deakin University,
Knowledge Systems Group, Department of Computer Science, University of Sydney,
Expert Systems Group - Continuum Australia Limited,
Key Centre for Knowledge Based Systems - RMIT, and
Department of Mathematics, Statistics, and Computing Science (UNE).
Hosted by
Department of Mathematics, Statistics, and Computing Science
The University of New England,Armidale, N.S.W., 2351, AUSTRALIA
AI'94 is the Seventh Australian Joint Conference on Artificial Intelligence.
The theme of the conference is "Sowing the Seeds for the Future", which reflects
the nature of research in Artificial Intelligence. The goal of the conference
is to promote research in artificial intelligence (AI) and scientific
interchange among AI researchers and practitioners. AI'94 will be hosted by
The Department of Mathematics, Statistics, and Computing Science at The
University of New England, between Monday 21st November and Friday 25th
November 1994. The conference programme will consist of formal tutorials and
workshops on the Monday and Tuesday, a Postgraduate session on Tuesday, and
technical paper presentation sessions from Wednesday 23rd to Friday 25th of
November. In addition to these sessions there will be three Keynote addresses
from renowned international speakers.
Wednesday, 23rd November : Professor Wolfgang Wahlster,
German Research Center for AI (DFKI)
Topic of address : Intellimedia: Planning Language, Graphics and
Layout for Adaptive Information Presentation
Wolfgang Wahlster is a Professor of Artificial Intelligence in the
Department of Computer Science at the University of Saarbruecken, Germany
where he currently serves as a Scientific Director of the German Research
Center for Artificial Intelligence (DFKI). Since 1975 he has been the
principal investigator in various language projects, including HAM-ANS,
WISBER, SC, XTRA, VITRA and WIP. He has published over 100 technical papers
on natural language processing. His current research includes intelligent
multimodal interfaces, user modeling, natural language scene description,
intelligent help systems, and deductive plan recognition and generation.
Prof. Wahlster is on the editorial boards of various international journals
and book series such as Artificial Intelligence, Applied Artificial
Intelligence, User Modeling and User-adapted Interaction, Symbolic
Computation and the MIT-ACL series. He is a AAAI Fellow and a recipient of
the Fritz Winter Award, one of the most prestigious awards for engineering
sciences in Germany, for his research on cooperative user interfaces. Prof.
Wahlster served as the Conference Chair for IJCAI-93 in Chambery and the
Chair of the Board of Trustees of IJCAII from 1991 -1993.
Thursday, 24th November : Professor Katia Sycara,
Carnegie Mellon University
Topic of address : The Present and Future of Distributed
Artificial Intelligence
Katia Sycara is a Research Scientist in the School of Computer Science at
Carnegie Mellon University. She is also Director of the Enterprise
Integration Laboratory. She is directing and conducting research aimed at
developing decision support systems for integrating organisational decision
making. Her doctoral research contributed to the definition of the
case-based reasoning paradigm. She has been Principal Investigator of
various government and industry funded research (e.g. distributed
scheduling, concurrent engineering, enterprise integration, case-based
Engineering design, crisis action planning). Dr. Sycara is the author of a
book on manufacturing and over 70 technical papers dealing with
negotiation, distributed problem solving, case-based reasoning, integration
of case-based reasoning with other problem solving methods, and
constraint-based reasoning. She is the Area Editor for AI and Management
Science for the journal "Group Decision and Negotiation" and on the
editorial board of "AI in Engineering" and "Concurrent Engineering:
Research and Applications". She is a member of AAAI, ACM, IEEE, and the
Institute for Management Science (TIMS).
Friday, 25th November : Professor John F. Sowa,
State University of New York - Binghamton
Topic of Address : Sharing and Integrating Knowledge Bases
John F. Sowa is the author of the book Conceptual Structures, which in the
past ten years has led to a world-wide movement of people who are using,
implementing, and extending the theory of conceptual graphs. He had been
working at IBM for 30 years on various aspects of computer systems design
and development, especially artificial intelligence and computational
linguistics. Now, he is teaching, writing, and working on standards for
conceptual schemas with the American National Standards Institute (ANSI)
and the International Standards Organization (ISO).
PROGRAM COMMITTEE
Dr. Chengqi Zhang (co-chair); UNE Dr. Dickson Lukose; UNE
Prof. John Debenham (co-chair); UTS Dr. Anand Rao; AAII
A/Prof. Mike Brooks; Adelaide A/Prof. Claude Sammut; UNSW
Dr. Jennie Clothier; DSTO A/Prof. Liz Sonenberg; Melbourne
Dr. Robert Dale; Microsoft Prof. Rodney Topor; Griffith
A/Prof. Wee Leng Goh; NTU, Singapore Dr. Wayne Wobcke; Sydney
Mr. Andy Horsfall; Fujitsu Dr. Xindong Wu; James Cook
Prof. Ray Jarvis; Monash Dr. Xin Yao; ADFA
Dr. Chris Leckie; TRL Dr. Waikiang Yeap; Otago, N.Z.
Dr. Craig Lindley; CSIRO A/Prof. David W. Russell, USA
ORGANISING COMMITTEE
Dr. Dickson Lukose (chair) Dr. Chengqi Zhang Mr. Prakash Bhandari
Mr. Allan Williams (secretary) Dr. Gregory Zevin Ms. Gabrielle Aldridge
We invite authors to submit papers describing both experimental and
theoretical results from all stages of AI research. We encourage submission of
papers that describe innovative concepts, techniques, perspectives, or
observations that are not yet supported by mature results. Such submissions
must include substantial analysis of the ideas, the technology needed to
realise them, and their potential impact. Papers describing applied AI are
particularly solicited. Topics of interest include, but are not limited to:
Machine Learning Distributed Artificial Intelligence
Knowledge Acquisition Artificial Intelligence Applications
Natural Language Generation Intelligent Decision Support Systems
Natural Language Understanding Cognitive Modeling
Hybrid Systems Robotics
Genetic Algorithms Vision
Evolutionary Programming Planning and Scheduling
Knowledge Based Systems Neural Network
Knowledge Representation Image Analysis
Qualitative Reasoning Automated Reasoning
Authors must submit five (5) copies of the completed paper to the AI'94
Conference Secretary, which should be received by or on 15th June 1994. All
five (5) copies of the submitted paper must be clearly legible. Neither
computer files nor fax submission are acceptable. Papers received after
15th June 1994 will be returned unopened. Notification of receipt will be
mailed to the first author (or designated author) soon after receipt.
PAPER FORMAT FOR REVIEW
All five copies of the submissions must be printed on 8 1/2" x 11" or A4
paper using 12 point type (10 characters per inch for typewriters or 12
point LaTeX article-style). The body of submitted papers must be at most 8
pages, including figures, tables, diagrams, and bibliography, but excluding
the title page. Papers exceeding the specified length or not conforming to
the formatting requirements are subject to rejection without review. Each
copy of the paper must have a title page (separate from the body of the
paper) containing the title of the paper, the names and addresses of all
authors, telephone number, fax number, electronic mail address, a short
(less than 200 word) abstract, topic, and a keyword list. The body of the paper
must also contain a copy of the title and abstract without any author
details. In addition each page within the paper must be clearly numbered.
To facilitate the reviewing process, authors are requested to select
their paper's keywords from the list below. Authors are invited to add
additional keywords to their keyword list if necessary.
Artificial Life, Automated Reasoning, Behaviour-Based Control, Belief
Revision, Case-Based Reasoning, Cognitive Modelling, Common Sense
Reasoning, Communication and Cooperation, Constraint-Based Reasoning,
Computer-Aided Education, Connectionist Models, Corpus-Based Language
Analysis, Deduction, Diagnosis, Discourse Analysis, Distributed Problem
Solving, Expert Systems, Geometrical Reasoning, Information Extraction,
Knowledge Acquisition, Knowledge Representation, Knowledge Sharing
Technology, Large Scale Knowledge Engineering, Learning/Adaptation, Machine
Learning, Machine Translation, Mathematical Foundations, Multi-Agent
Planning, Natural Language Processing, Neural Networks, Nonmonotonic
Reasoning, Perception, Planning, Probabilistic Reasoning, Qualitative
Reasoning, Reasoning about Action, Reasoning about Physical Systems,
Reactivity, Robot Navigation, Robotics, Rule-Based Reasoning, Scheduling,
Search, Sensor Interpretation, Sensory Fusion/Fission, Simulation, Situated
Cognition, Spatial Reasoning, Speech Recognition, System Architectures,
Temporal Reasoning, Terminological Reasoning, Theorem Proving, Truth
Maintenance, User Interfaces, Virtual Reality, Vision, 3-D Model
Acquisition.
Each paper will be carefully reviewed. The criteria that will be given to the
conference reviewers have been reproduced below. Authors are advised to bear
these criteria in mind while writing their papers: How important is the work
reported? Does it attack an important/difficult problem or a
peripheral/simple one? Does the approach offered advance the state of the
art? Has this or similar work been previously reported? Are the problems
and approaches completely new? Is this a novel combination of familiar
techniques? Does the paper point out differences from related research? Is
it re-inventing the wheel using new terminology? Is the paper technically
sound? Does it carefully evaluate the strengths and limitations of its
contribution? How are its claims backed up? Is the paper clearly written?
Does it motivate the research? Does it describe clearly the algorithms or
techniques employed? Does the paper describe previous work? Are the results
described and evaluated? Is the paper organised in a logical fashion?
PROCEEDINGS PUBLICATION
The proceedings of AI'94 will be published by World Scientific Publishers.
IMPORTANT DATES
Deadline for paper submission : 15th June 1994
Notification of acceptance : 31st July 1994
Camera Ready Copy : 22nd August 1994
Conference : 21st - 25th November 1994
FURTHER INFORMATION
All enquires regarding AI'94 and papers submitted to AI'94 should be directed
to the following address:
AI'94 Conference Secretary
Department of Mathematics, Statistics, and Computing Science
The University of New England, Armidale, N.S.W., 2351, AUSTRALIA
E-mail: ai94@fermat.une.edu.au
You may e-mail the following address with the Subject Heading "help" to
obtain details on AI'94, UNE, and Armidale.
ai94-info@fermat.une.edu.au
ai94-info mail server has been established to enable electronic request for
information regarding AI'94 Conference.
-------------------------------------------------------------------------------
IMPORTANT DATES FOR AI'94 WORKSHOPS
-------------------------------------------------------------------------------
a) 1st Australian Conceptual Structures Workshop
Submission Deadline August 31, 1994.
Notification of Acceptance September 30, 1994.
Camera-ready copy October 15, 1994.
b) AI'94 Workshop on Evolutionary Computation
Submission Deadline August 8, 1994.
Notification of Acceptance September 12, 1994.
Camera-ready copy October 17, 1994.
c) AI'94 Workshop on Expert Systems in Production use
Abstarct Submission Deadline August 31, 1994.
Notification of Acceptance September 15, 1994.
d) AI'94 Workshop on Knowledge-Based Systems in Natural Resource Management
Abstarct Submission Deadline August 31, 1994.
Notification of Acceptance September 15, 1994.
e) 2nd Australian Workshop on Natural Language Processing
Submission of extended abstract August 9, 1994
Notification of acceptance: September 16, 1994
Full paper submission: October 17, 1994
-------------------------------------------------------------------------------
-------------------------------------------------------------------------------
STRUCTURED SEQUENCE TUTORIALS
-------------------------------------------------------------------------------
A structured sequence of pre-conference tutorials on several aspects of
applied AI has been organised. Tutorial participants will be able to select
from a choice of tutorials to suit their specialist requirements.
The following are the list of tutorials organised for AI'94. All
participants of any of these tutorials may attend the talk entitled
"Introduction to Artificial Intelligence". This is a complementary session
for all tutorial participants.
Guide:
(y) - indicate YES
(n) - indicate NO
(t) - indicate THEORETICAL SESSION
(p) - indicate PRACTICAL SESSION
(d) - indicate DEMONSTRATION SESSION
1hr - indicate one hour
4s - indicate four sessions
3s - indicate three sessions
Note: Each session is One and a Half hours long.
--------------------------------------------------------------------------------
No. Tutorial Title Presenters CODE Length Practical
--------------------------------------------------------------------------------
[0] Introduction To Artificial Not Confirmed yet AI 1hr -
Intelligence
[1] Constraint-Based Reasoning Dr. H. W. Guesgen CBR 4s y
[2] Fundamentals of Fuzzy Logic Dr. A. Sekercioglu FLFC 3s y
and Fuzzy Logic Controllers G.K. Egan
[3] An Introduction to Evolutionary Dr. X. Yao EC 3s y
Computation
[4] Building Intelligent Decision Dr. J. Zeleznikow IDSS 3s y
Support Systems through the use Mr. Dan Hunter
of multiple reasonig Strategies
[5] Intelligent Learning Database Dr Xindong Wu ILDB 3s y
Systems
[6] Nonmonotonic Reasoning Dr. M-A Williams NMR 3s y
Dr. G. Antoniou
[7] Theoretical Foundations of Dr. A. G. Hoffman TFML 3s n
Machine Learning Dr. Shyam Kapur
Dr. Arun Sharma
[8] Knowledge Acquisition and Dr. P. Compton KAM 3s d
Maintenance with Ripple Down
Rules
[9] Hybrid (AI symbolic, Dr. Nik K. Kasabov HS 3s d
Connectionist, Fuzzy, Chaotic)
Systems
--------------------------------------------------------------------------------
Tentative Tutorial Timetable
--------------------------------------------------------------------------------
Monday 21/11/94 (Day 1)
=======================
9.30 - 10.30: Introduction to AI
10.30 - 11.00: Morning Tea Break
11.00 - 12.30: NMR(t) IDSS(t) EC(t) TFML(t)
12.30 - 2.00: Lunch
2.00 - 3.30: NMR(t) IDSS(t) EC(t) TFML(t)
3.30 - 4.00: Afternoon Tea Break
4.00 - 5.30: NMR(p) IDDS(p) EC(p) TFML(t)
Tuesday 22/11/94 (Day 2)
========================
9.00 - 10.30: CBR(t) ILDB(t) FLFC(t) KAM(t) HS(t)
10.30 - 11.00: Morning Tea Break
11.00 - 12.30: CBR(t) ILDB(t) FLFC(t) KAM(t) HS(t)
12.30 - 2.00: Lunch
2.00 - 3.30: CBR(t) ILDB(p) FLFC(p) KAM(d) HS(d)
3.30 - 4.00: Afternoon Tea Break
4.00 - 5.30: CBR(p)
--------------------------------------------------------------------------------
Examples of structured sequence of tutorials:
--------------------------------------------------------------------------------
There are couple of structured sequence of tutorials that one could adopt.
For example, if the participant is interested in logic/theoretical basis of
AI, then he/she may want to select the following sequence:
Day 1 9.30 - 10.30: Introdution to AI
11.00 - 12.30: NMR(t)
2.00 - 3.30: NMR(t)
4.00 - 5.30: NMR(p)
Day 2 9.00 - 10.30: CBR(t)
11.00 - 12.30: CBR(t)
2.00 - 3.30: CBR(t)
4.00 - 5.30: CBR(p)
Alternatively, if the participant is more interested in the applications of
AI, then the following sequence may be more suitable:
Day 1 9.30 - 10.30: Introdution to AI
11.00 - 12.30: IDSS(t)
2.00 - 3.30: IDSS(t)
4.00 - 5.30: IDSS(p)
Day 2 9.00 - 10.30: FLFC(t)
11.00 - 12.30: FLFC(t)
2.00 - 3.30: FLFC(p)
If the interest is in Machine Learning/Knowledge Acquisition, then the
possible sequence may be:
Day 1 9.30 - 10.30: Introdution to AI
11.00 - 12.30: TFML(t)
2.00 - 3.30: TFML(t)
4.00 - 5.30: TFML(t)
Day 2 9.00 - 10.30: ILDB(t) or KAM(t)
11.00 - 12.30: ILDB(t) or KAM(t)
2.00 - 3.30: ILDB(p) or KAM(d)
Another possible sequence may be:
Day 1 9.30 - 10.30: Introdution to AI
11.00 - 12.30: EC(t)
2.00 - 3.30: EC(t)
4.00 - 5.30: EC(p)
Day 2 9.00 - 10.30: HS(t)
11.00 - 12.30: HS(t)
2.00 - 3.30: HS(d)
--------------------------------------------------------------------------------
Further Information:
--------------------------------------------------------------------------------
For further information on the structured sequence tutorials, please
contact the AI'94 Tutorial Co-ordinator, at the following address:
Dr. Dickson Lukose
Department of Mathematics, Statistics, and Computing Science
University of New England
Armidale, N.S.W., 2351
AUSTRALIA
e-mail: ai94@fermat.une.edu.au
fax. : (+61 67) 73 3312
--------------------------------------------------------------------------------
-----------------------------------------------------------------------
To: comp-ai-nlang-know-rep@munnari.OZ.AU
From: ai94@fermat.une.edu.au (Artificial Intelligence Conference 1994)
Subject: CFP: AI'94 TUTORIAL ON INTELLIGENT LEARNING DATABASE SYSTEMS
Date: 18 May 94 08:31:24 GMT
Seventh Australian Joint Conference on Artificial Intelligence (AI'94)
"Sowing the Seeds for the Future"
C A L L F O R P A R T I C I P A T I O N S
AI'94 Tutorial on Intelligent Learning Database Systems
by
Dr Xindong Wu
Dept. of Computer Science, James Cook University,
Townsville, Queensland 4811, Australia
xindong@coral.cs.jcu.edu.au
22 November 1994
ABSTRACT
Knowledge acquisition from databases is a research frontier for both database
technology and machine learning (ML) techniques, and has seen sustained
research over recent years. It also acts as a link between the two fields,
thus offering a dual benefit. Firstly, since database technology has already
found wide application in many fields, ML research obviously stands to gain
from this greater exposure and established technological foundation. Secondly,
ML techniques can augment the ability of existing database systems to
represent, acquire, and process a collection of expertise such as those which
form part of the semantics of many advanced applications (e.g. CAD/CAM). This
full-day tutorial will present and discuss techniques for the following 3
interconnected phases in constructing intelligent learning database systems:
(1) Translation of standard database information into a form suitable for use
by a rule-based system; (2) Using machine learning techniques to produce rule
bases from databases; and (3) Interpreting the rules produced to solve users'
problems and/or reduce data spaces. It will suit a wide audience (including
postgraduate students and industrial people) from databases, expert systems,
and machine learning.
CONTENTS
1. Knowledge Acquisition from Databases: Problem and Domain
1.1 Problems in Conventional Databases
1.2 Research Topics in Intelligent Databases
1.3 Requirements for Knowledge Discovery in Databases
2. Typical Inductive Learning Algorithms
2.1 The ID3 Family
2.2 The AQ Family
2.3 The HCV Family
3. Integrating More Semantic Information into Data Models
3.1 The E-R Model
3.2 Deductive and Object-Oriented Databases
3.3 More Expressive Representations
4. An Intelligent Learning Database System
To introduce a PC shell developed at Edinburgh
5. Conclusions and Research Directions in the Field
6. A Practical Component Using a PC Lab
COURSE MATERIAL
- Xindong Wu, Research Issues in Intelligent Learning Database Systems,
Proceedings of the Seventh Annual Florida AI Research Symposium, Pensacola
Beach, Florida, U.S.A., May 5-7, 1994, 137--141.
- Xindong Wu, Inductive Learning: Algorithms and Frontiers, Artificial
Intelligence Review, 7(1993), 2: 93-108.
- Xindong Wu, KEshell2: An Intelligent Learning Data Base System, Research and
Development in Expert Systems IX, M.A. Bramer and R.W. Milne (Eds.),
Cambridge University Press, U.K., 1992, 253--272.
BIO-DATA OF THE PRESENTER
Dr Xindong Wu received his first and Master's degrees in Computer Science from
Hefei University of Technology, China, and his Ph.D. in Artificial Intelligence
from the University of Edinburgh, Britain. In the past, he has authored 2
technical books, Expert Systems Technology (1988) and Constructing Expert
Systems (1990). He has also published over 60 papers in various periodicals
(such as Expert Systems: The International Journal of Knowledge Engineering,
Artificial Intelligence Review, Informatica, and the Journal of Computer
Science and Technology) and in conference proceedings (e.g., Research and
Development in Expert Systems IX, and the 21st ACM Computer Science
Conference). His technical interests include machine learning, expert systems,
intelligent database systems, and knowledge-based software engineering. He is
an editor on the Editorial Board of the Europe-based Informatica: An
International Journal of Computing and Informatics, and a member of the
Editorial Board of the U.S.A.-based International Journal of Computers and
Their Applications. He has taught courses in Combinatorial Mathematics,
Expert Systems, Knowledge Representation and Inference, Machine Learning,
Advanced Data Structures and Databases, Introduction to Computer Science, and
Artificial Intelligence.
PREREQUISITES
Databases, Expert Systems, and (preferably) Prolog.
-------------------------------------------------------------------------------
Seventh Australian Joint Conference on Artificial Intelligence (AI'94)
STRUCTURED SEQUENCE TUTORIALS
A structured sequence of pre-conference tutorials on several aspects of
applied AI has been organised. Tutorial participants will be able to select
from a choice of tutorials to suit their specialist requirements.
The following are the list of tutorials organised for AI'94. All
participants of any of these tutorials may attend the talk entitled
"Introduction to Artificial Intelligence". This is a complementary session
for all tutorial participants.
Guide:
(y) - indicate YES
(n) - indicate NO
(t) - indicate THEORETICAL SESSION
(p) - indicate PRACTICAL SESSION
(d) - indicate DEMONSTRATION SESSION
1hr - indicate one hour
4s - indicate four sessions
3s - indicate three sessions
Note: Each session is One and a Half hours long.
--------------------------------------------------------------------------------
No. Tutorial Title Presenters CODE Length Practical
--------------------------------------------------------------------------------
[0] Introduction To Artificial Not Confirmed yet AI 1hr -
Intelligence
[1] Constraint-Based Reasoning Dr. H. W. Guesgen CBR 4s y
[2] Fundamentals of Fuzzy Logic Dr. A. Sekercioglu FLFC 3s y
and Fuzzy Logic Controllers G.K. Egan
[3] An Introduction to Evolutionary Dr. X. Yao EC 3s y
Computation
[4] Building Intelligent Decision Dr. J. Zeleznikow IDSS 3s y
Support Systems through the use Mr. Dan Hunter
of multiple reasonig Strategies
[5] Intelligent Learning Database Dr Xindong Wu ILDB 3s y
Systems
[6] Nonmonotonic Reasoning Dr. M-A Williams NMR 3s y
Dr. G. Antoniou
[7] Theoretical Foundations of Dr. A. G. Hoffman TFML 3s n
Machine Learning Dr. Shyam Kapur
Dr. Arun Sharma
[8] Knowledge Acquisition and Dr. P. Compton KAM 3s d
Maintenance with Ripple Down
Rules
[9] Hybrid (AI symbolic, Dr. Nik K. Kasabov HS 3s d
Connectionist, Fuzzy, Chaotic)
Systems
--------------------------------------------------------------------------------
Tentative Tutorial Timetable
--------------------------------------------------------------------------------
Monday 21/11/94 (Day 1)
=======================
9.30 - 10.30: Introduction to AI
10.30 - 11.00: Morning Tea Break
11.00 - 12.30: NMR(t) IDSS(t) EC(t) TFML(t)
12.30 - 2.00: Lunch
2.00 - 3.30: NMR(t) IDSS(t) EC(t) TFML(t)
3.30 - 4.00: Afternoon Tea Break
4.00 - 5.30: NMR(p) IDDS(p) EC(p) TFML(t)
Tuesday 22/11/94 (Day 2)
========================
9.00 - 10.30: CBR(t) ILDB(t) FLFC(t) KAM(t) HS(t)
10.30 - 11.00: Morning Tea Break
11.00 - 12.30: CBR(t) ILDB(t) FLFC(t) KAM(t) HS(t)
12.30 - 2.00: Lunch
2.00 - 3.30: CBR(t) ILDB(p) FLFC(p) KAM(d) HS(d)
3.30 - 4.00: Afternoon Tea Break
4.00 - 5.30: CBR(p)
--------------------------------------------------------------------------------
Examples of structured sequence of tutorials:
--------------------------------------------------------------------------------
There are couple of structured sequence of tutorials that one could adopt.
For example, if the participant is interested in logic/theoretical basis of
AI, then he/she may want to select the following sequence:
Day 1 9.30 - 10.30: Introdution to AI
11.00 - 12.30: NMR(t)
2.00 - 3.30: NMR(t)
4.00 - 5.30: NMR(p)
Day 2 9.00 - 10.30: CBR(t)
11.00 - 12.30: CBR(t)
2.00 - 3.30: CBR(t)
4.00 - 5.30: CBR(p)
Alternatively, if the participant is more interested in the applications of
AI, then the following sequence may be more suitable:
Day 1 9.30 - 10.30: Introdution to AI
11.00 - 12.30: IDSS(t)
2.00 - 3.30: IDSS(t)
4.00 - 5.30: IDSS(p)
Day 2 9.00 - 10.30: FLFC(t)
11.00 - 12.30: FLFC(t)
2.00 - 3.30: FLFC(p)
If the interest is in Machine Learning/Knowledge Acquisition, then the
possible sequence may be:
Day 1 9.30 - 10.30: Introdution to AI
11.00 - 12.30: TFML(t)
2.00 - 3.30: TFML(t)
4.00 - 5.30: TFML(t)
Day 2 9.00 - 10.30: ILDB(t) or KAM(t)
11.00 - 12.30: ILDB(t) or KAM(t)
2.00 - 3.30: ILDB(p) or KAM(d)
Another possible sequence may be:
Day 1 9.30 - 10.30: Introdution to AI
11.00 - 12.30: EC(t)
2.00 - 3.30: EC(t)
4.00 - 5.30: EC(p)
Day 2 9.00 - 10.30: HS(t)
11.00 - 12.30: HS(t)
2.00 - 3.30: HS(d)
--------------------------------------------------------------------------------
Further Information:
--------------------------------------------------------------------------------
For further information on the structured sequence tutorials, please
contact the AI'94 Tutorial Co-ordinator, at the following address:
Dr. Dickson Lukose
Department of Mathematics, Statistics, and Computing Science
University of New England
Armidale, N.S.W., 2351
AUSTRALIA
e-mail: ai94@fermat.une.edu.au
fax. : (+61 67) 73 3312
--------------------------------------------------------------------------------
End of NL-KR Digest
*******************
