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AIList Digest Volume 4 Issue 028
AIList Digest Monday, 17 Feb 1986 Volume 4 : Issue 28
Today's Topics:
Seminars - A Design System for Engineering (MIT) &
Fuzzy Logic and Common Sense Knowledge (SD Sigart) &
Knowledge Engineering, Ontology (Oregon State) &
Explanation-Based Learning (MIT) &
Reactive Systems (SRI) &
Temporal Logic for Concurrent Programs (CMU),
Course - Spring Quarter Seminar on Rule-Based Systems (SU)
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Date: 13 Feb 1986 10:39 EST (Thu)
From: Claudia Smith <CLAUDIA%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU>
Subject: Seminar - A Design System for Engineering (MIT)
[Forwarded from the MIT bboard by SASW@MIT-MC.]
AN INTEGRATED DESIGN SYSTEM
FOR ENGINEERING
Robin J. Popplestone
Edinburgh University
Scotland
I discuss the representation of mechanical engineering designs in a
Logic programming context, and the exploration of a space of different
possible designs. Designs are represented in terms of modules, which
are basic concrete engineering entities (eg. motor, keyway, shaft).
Modules interact via ports, and have an internal structure expressed
by the part predicate. A taxonomic organisation of modules is used as
the basis for making design decisions. Subsystems employed by the
design system include the spatial relational inference mechanism
employed in the RAPT robot Language, the Noname geometric modeller
developed at Leeds University and the Press symbolic equation solver.
The system is being implemented in the POPLOG system. An assumption
based truth maintenance system based on the work of de Kleer is being
implemented to support the exploration of design space.
Tuesday, Feb. 18, 1986
4pm
NE43, 8th Floor Playroom
Hosts: Professors Brooks and Lozano-Perez.
------------------------------
Date: 14 Feb 86 09:01 PST
From: sigart@LOGICON.ARPA
Subject: Seminar - Fuzzy Logic and Common Sense Knowledge (SD Sigart)
The San Diego SIGART presents
FUZZY LOGIC AND COMMON SENSE KNOWLEDGE
Featured Speaker:
Dr. Lotfi A. Zadeh
Thursday, Feb 20, 1986
6:30-8:30pm at UCSD
Humanities Library Rm. 1438
Dr.Zadeh will introduce the concept of a disposition and the principle
that common sense knowledge is of a dispositional nature, i.e. we can
infer dispositional rules which are true in most cases.
The concept of dispositionality leads to the concept of usuality or the
usual value of variables. We need to develop a system for computing
with and inferring from dispositional knowledge. Dr. Zadeh will show
how to use fuzzy logic to deal with the concepts of dispositionality
and usuality in a way which cannot be done with classical logic. Fuzzy
logic will therefore be shown to provide a framework for commonsense
reasoning.
------------------------------
Date: Thu, 13 Feb 86 09:46:27 pst
From: Tom Dietterich <tgd%oregon-state.csnet@CSNET-RELAY.ARPA>
Subject: Seminar - Knowledge Engineering, Ontology (Oregon State)
KNOWLEDGE ENGINEERING AS THE INVESTIGATION
OF ONTOLOGICAL STRUCTURE
Michael J. Freiling
Tektronix Laboratories
Beaverton, Oregon
Wednesday, February 12, l986
Cordley Hall, Room 1109
Oregon State University
Corvallis, Oregon
Experience has shown that much of the difficulty of learning to build
knowledge-based systems lies in learning to design representation structures
that adequately capture the necessary forms of knowledge. Ontological
analysis is a method we have found quite useful at Tektronix for analyzing
and designing knowledge-based systems. The basic approach of ontological
analysis is a step-by-step construction of knowledge structures beginning
with basic objects and relationships in the task domain, and continuing
through representations of state, state transformations, and heuristics for
selecting transformations. Formal tools that can be usefully employed in
ontological analysis include domain equations, semantic grammars, and
full-scale specification languages. The principles and tools of ontological
analysis are illustrated with actual examples from knowledge-based systems
we have built or analyzed with this method.
------------------------------
Date: Fri, 14 Feb 86 15:20 EST
From: Brian C. Williams <WILLIAMS@OZ.AI.MIT.EDU>
Subject: Seminar - Explanation-Based Learning (MIT)
[Forwarded from the MIT bboard by SASW@MIT-MC.]
Thursday , February 20 4:00pm Room: NE43- 8th floor Playroom
The Artificial Intelligence Lab
Revolving Seminar Series
Explanation-Based Learning
Tom Mitchell
Rutgers University, New Brunswick, NJ
The problem of formulating general concepts from specific training
examples has long been a major focus of machine learning research.
While most previous research has focused on empirical methods for
generalizing from a large number of training examples using no
domain-specific knowledge, in the past few years new methods have been
developed for applying domain-specific knowledge to formulate valid
generalizations from single training examples. The characteristic
common to these methods is that their ability to generalize from a
single example follows from their ability to explain why the training
example is a member of the concept being learned. This talk proposes a
general, domain-independent mechanism, call EBG, that unifies previous
approaches to explanation-based generalization. The EBG method is
illustrated in the context of several example problems, and used to
contrast several existing systems for explanation-based generalization.
The perspective on explanation-based generalization afforded by this
general method is also used to identify open research problems in this
area.
------------------------------
Date: Fri 14 Feb 86 18:27:38-PST
From: LANSKY@SRI-AI.ARPA
Subject: Seminar - Reactive Systems (SRI)
AN ARCHITECTURE FOR INTELLIGENT REACTIVE SYSTEMS
OR
HOW NOT TO BE EATEN BY A TIGER
Leslie Kaelbling
SRI International AI Center and Stanford University
11:00 AM, WEDNESDAY, February 19
SRI International, Building E, Room EJ228 (new conference room)
In this talk I will present an architecture for intelligent reactive
systems. The ideas are fairly general, but are intended for use in
programming Flakey to carry out complex tasks in a dynamic environment.
Many previous robots simply 'closed their eyes' while a time-consuming
system, such as a planner or vision system, was invoked, allowing
perceptual inputs either to be lost or saved for later processing. In a
truly dynamic world, things might change to such an extent that the
results of the long calculation would no longer be useful. Worse yet,
the robot might run into a wall or be eaten by a tiger. This
architecture will allow the robot to remain aware during long
computations, and to behave plausibly in novel situations.
This talk represents work in progress, so much of the seminar will
be devoted to general discussion.
------------------------------
Date: 14 February 1986 1045-EST
From: Cathy Hill@A.CS.CMU.EDU
Subject: Seminar - Temporal Logic for Concurrent Programs (CMU)
Speaker: Aravinda Prasad Sistla <aps0%gte-labs.csnet@CSNET-RELAY.ARPA>
Date: February 19, 1986
Time: 1:30 - 3:00 pm
Place: WeH 4623
Title: ON EXPRESSING SAFETY AND LIVENESS PROPERTIES IN TEMPORAL
LOGIC.
Correctness properties of concurrent programs are usually classified as
either safety properties or liveness properties. In general, proving a program
correct involves in establishing that the program satisfies certain safety
properties and certain liveness properties, and usually different techniques
are applied in proving these properties. In this talk we consider many
different definitions of these properties (e.g. safety,strong safety,liveness,
absolute liveness etc.) and investigate what classes of these properties are
expressible in temporal logic. We present syntactic characterization of
formulae that express these properties. Finally, we give algorithms to
recognize if a temporal specification is a safety property or liveness
property.
------------------------------
Date: Wed 12 Feb 86 15:47:58-PST
From: Ted Shortliffe <Shortliffe@SUMEX-AIM.ARPA>
Subject: Course - Spring Quarter Seminar on Rule-Based Systems (SU)
[Forwarded from the Stanford bboard by Laws@SRI-AI.]
SEMINAR ON RULE-BASED EXPERT SYSTEMS
Professors Buchanan and Shortliffe
Comp. Sci. 524 Med. Inf. Sci. 229
Spring Quarter 1986 - 2 units
Tuesday, 3:30-5:00PM
TC-135 Conference Room, Medical Center
[Class size limited to 16]
This course is a graduate seminar for students wishing to gain a technical
understanding of, as well as a historial perspective on, rule-based expert
systems. The emphasis of the course will be on an analysis of the research
lessons of MYCIN and related projects in the Knowledge Systems Laboratory,
the strengths and limitations of the rule-based approach to knowledge
representation, and the way in which AI research evolves as new ideas and
concepts are discovered.
The course will meet weekly for 90 minutes and will require substantial
reading assignments for each session. The required text for the seminar is
"Rule-Based Expert Systems: The MYCIN Experiments of the Stanford Heuristic
Programming Project"; additional related papers will also be assigned.
Working in pairs, all students will be responsible for leading the discussion
once during the quarter. There will be a final exam.
Prerequisites: at least one course in artificial intelligence and
familiarity with LISP.
Enrollment: limited to 16; signup in TC-135 or by contacting Ms.
Alison Grant (GRANT@SUMEX or 7-6979). If the course is
oversubscribed, preference will be given as follows:
MS/AI and MIS grad students, other CSD grad students,
non-CSD graduate students and medical students, CSD
research staff, undergraduates, auditors.
2 units, Tu 3:30-5:00, Room TC-135 (Medical Center), Professors
Buchanan and Shortliffe. The course will not be
offered again until 1987-88.
April 1: INTRODUCTION
Readings: None
April 8: KNOWLEDGE ENGINEERING
Readings: Chapters 1,7,35,8,9 [Chapter 4 suggested before 7 for
those unfamiliar with MYCIN]
April 15: USING RULES
Readings: Chapters 2,3,5,6
April 22: REASONING UNDER UNCERTAINTY
Readings: Chapters 10,11,12,13 [updated version of Chapter 13 will
be provided]
April 29: GENERALIZED FRAMEWORKS
Readings: Chapters 14,15,16,33
May 6: OTHER REPRESENTATIONS OF KNOWLEDGE
Readings: Chapters 21,22,23,24
May 13: EXPLANATIONS/TUTORING
Readings: Chapters 17,18,20,25,26
May 20: META-LEVEL KNOWLEDGE
Readings: Chapters 27,28,29
May 22 (Thursday class, 3:30-5pm): EVALUATING PERFORMANCE
Readings: Chapters 30,31
May 27: no class
Readings: Chapters 32,34,36
June 3: SUMMARY AND CONCLUSIONS
Readings: None
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End of AIList Digest
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