[mod.techreports] st12.x tech reports

E1AR0002@SMUVM1.BITNET (11/11/86)

TECHNICAL NOTE:  246\hfill PRICE:  \$16.00\\[0.01in]

\noindent TITLE:  DEDUCTIVE SYNTHESIS OF THE UNIFICATION ALGORITHM\\
AUTHORS:  ZOHAR MANNA and RICHARD WALDINGER\\
DATE:  JULY 1981\\[0.01in]

     ABSTRACT: The deductive approach is a formal program construction
method in which the derivation of a program from a given specification
is  regarded as a theorem-proving task.   To construct a program whose
output satisfies   the conditions  of the specification,  we   prove a
theorem  stating   the  existence of such  an   output.  The proof  is
restricted to be sufficiently constructive so that a program computing
the desired output  can  be extracted directly  from  the proof.   The
program we obtain is  applicative and may  consist of several mutually
recursive procedures.   The proof constitutes  a demonstration of  the
correctness of this program.

     To exhibit the full power of the deductive approach,  we apply it
to a nontrivial  example--the  synthesis of  a unification  algorithm.
Unification is the process  of  finding a  common  instance  of  two
expressions.  Algorithms to  perform unification have been central  to
many   theorem-proving    systems and   to some  programming-language
processors.

     The  task of  deriving a  unification  algorithm automatically is
beyond the power of existing program synthesis systems.  In this paper
we use the  deductive  approach to derive  an algorithm from a simple,
high-level specification of  the unification task.   We will identify
some  of  the  capabilities required  of  a theorem-proving  system to
perform this derivation automatically.\\
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TECHNICAL NOTE:  248\hfill PRICE:  \$10.00\\[0.01in]

\noindent TITLE:  ARTIFICIAL INTELLIGENCE:  ENGINEERING, SCIENCE OR SLOGAN?\\
AUTHOR:  NILS J. NILSSON\\
DATE:  JULY 1981\\[0.01in]

     ABSTRACT:  This  paper   presents    the  view   that  artificial
intelligence (AI) is primarily  concerned with propositional languages
for representing knowledge and  with techniques for manipulating these
representations.   In  this  respect,    AI is analogous   to  applied
mathematics;  its representations and techniques can  be applied in  a
variety of other subject areas.  Typically, AI research  is (or should
be)  more  concerned  with   the  general  form    and  properties  of
representational languages  and  methods than  it is with  the content
being   described  by  these languages.     Notable exceptions involve
commonsense'' knowledge about  the everyday world (no other  specialty
claims this subject  area as its  own), and world  (no knowledge about
the properties  and uses of  knowledge itself).  In  these areas AI is
concerned with content as  well as  form.   We also  observe that  the
technology   that   seems to    underlie peripheral sensory  and motor
activities (analogous to low-level animal  or human vision and  muscle
control) seems to be quite different from the technology that seems to
underlie cognitive reasoning and problem solving.  Some definitions of
AI would include peripheral  as well  as cognitive processes;  here we
argue against including the peripheral processes.\\
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TECHNICAL NOTE:  251\hfill PRICE: \$14.00\\[0.01in]

\noindent TITLE:  PRACTICAL NATURAL LANGUAGE PROCESSING BY COMPUTER\\
AUTHOR:  ROBERT C. MOORE\\
DATE:  OCTOBER 1981\\[0.01in]

     ABSTRACT: This paper describes the state of  the art in practical
computer systems  for natural-language processing.   We first consider
why  one  would  want  to use  natural language  to   communicate with
computers  at  all, looking   at  both  general  issues  and  specific
applications.  Next  we examine what  it really  means for a system to
have a natural-language capability.  This is followed by  a discussion
of  some  major limitations of current   technology.  The  bulk of the
paper is  devoted  to looking in  detail at  a  single  application of
natural-language  processing: database  retrieval by  natural-language
query.  We lay  out an overall  system architecture,  explaining  what
types of processing and information are required.  Then we look at two
general classes   of systems, special-purpose    and  general-purpose,
explaining how   they  differ  and   their   relative   advantages and
disadvantages.  Afterwards we  point out some remaining problems  that
will require addition  basic  research.   Finally    we   conclude  by
discussing  when language-processing  technology at various levels  of
capability is likely  to be commercially  practical, and  what is  may
cost to develop and use applications of that technology.\\
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TECHNICAL NOTE:  252\hfill PRICE:  \$12.00\\[0.01in]

\noindent TITLE:  MACHINE LEARNING FOR INFORMATION MANAGEMENT\\
AUTHORS:  NORMAN HAAS and GARY HENDRIX\\
DATE:  JULY 1981\\[0.01in]

     ABSTRACT: This paper discusses machine learning in the context of
information  management.  The core idea is  that  of a compiler system
that can hold a conversation with a user in English about his specific
domain  of  interest,  subsequently  retrieve and  display information
conveyed by the user, and  apply various types  of  external  software
systems to solve user problems.

     The specific   learning  problems discussed  is   how  to  enable
computer systems to acquire information about  domains with which they
are unfamiliar from people who  are expert  in those domains, but have
little  or no training  in  computer  science.  The information  to be
acquired  is    that needed  to   support  question-answering  or fact
retrieval tasks, and the  type of learning to  be employed is learning
by  being told.  Reflecting  the intimate connection between  language
and reasoning, this paper  is  largely concerned with the  problems of
learning concepts and language simultaneously.\\
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TECHNICAL NOTE:  253\hfill PRICE:  \$20.00\\[-0.15in]
\begin{tabbing}
\noindent TITLE: \= COMPUTATIONAL STRATEGIES FOR ANALYZING THE ORGANIZATION\\
             \> AND USE OF INFORMATION\\
AUTHOR:  DONALD E. WALKER\\
DATE:  JULY 1981\\[-0.15in]
\end{tabbing}

     ABSTRACT:  This    chapter   describes    new   developments   in
computer-based procedures that  can improve our  understanding  of how
people organize  and  use information.   Relevant   recent research in
information science,     computational   linguistics,  and  artificial
intelligence is reviewed.  A program of  research is presented that is
producing systems that make it possible to study  the organization and
use  of  information and, at   the same   time, provide more effective
support for people engaged in those activities.\\
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TECHNICAL NOTE:  254\hfill PRICE:  \$20.00\\[0.01in]

\noindent TITLE:  A TEAM USER'S GUIDE\\
AUTHORS:  ARMAR A. ARCHBOLD, BARBARA GROSZ, and DANIEL SAGALOWICZ\\
DATE:  DECEMBER 1981\\[0.01in]

     ABSTRACT: TEAM  (Transportable English Data Access  Manager) is a
computer system designed  to  acquire information  about a  (local  or
remote) database,  and subsequently to interpret and  answer questions
addressed to the database in a subset of natural language.

     The  system   currently includes  an   interactive  program  that
acquires information about a database from the database administrator.
The user  is  asked how the  database is  to  be  structured  and what
language   is to be used to   talk about its    contents.  The program
augments the following  components  of a  core natural language access
system:

       *  The lexicon

    *  The conceptual model of the domain (or conceptual schema)

    *  The structural model of the database (or database schema).

     After  these steps  have   been  completed, the   system  accepts
natural-language questions   about the  database contents  and, to the
EXTENT it is able, provides relevant responses.\\
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TECHNICAL NOTE:  255\hfill PRICE:  \$14.00\\[0.01in]

\noindent TITLE:  THE DATABASE AS MODEL:  A METATHEORETIC APPROACH\\
AUTHOR:  KURT KONOLIGE\\
DATE:  SEPTEMBER 1981\\[0.01in]

     ABSTRACT: This paper presents  a method  of formally representing
the information that is available to a user of a  relational database.
The intended application area is deductive question-answering  systems
that  must  access  an  existing relational    database.   To  respond
intelligently  to user  inquiries,  such  systems   must  have a  more
complete representation of the domain of discourse than is generally
available in the tuple sets of a relational database.  Given this more
expressive representation, the problem then arises of how to reconcile
the   information   present  in the    database  with   the   domain
representation, so that database queries can be  derived to answer the
user's inquiries.  Here we take  the formal approach  of describing  a
relational database as the model  of a  first-order language.  Another
first-order language, the metalanguage, is used both  to represent the
domain of discourse, and to describe the relationship of  the database
to the  domain.  The formal advantages  of this approach are presented
and contrasted with other work in the area.\\
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TECHNICAL NOTE:  256\hfill PRICE:  \$14.00\\[0.01in]

\noindent TITLE:  A PROBABILISTIC MODEL FOR UNCERTAIN PROBLEM SOLVING\\
AUTHOR:  ARTHUR M. FARLEY\\
DATE:  DECEMBER 1981\\[0.01in]

     ABSTRACT: With growing interest in the application of research to
problems  that   arise  in   real-world  contexts,   issues raised  by
consideration   of  uncertain states  and    unreliable  operators are
receiving increased attention in artificial intelligence research.  In
this paper, a model is presented for  dealing with such concerns.  The
model is  a  probabilistic  generalization of the  familiar  notion of
problem space.   The specification of  uncertain states and unreliable
operators is discussed.  Problem-solving search methods are described.
The need for information gathering is established.  Search methods are
generalized to produce tree-structured plans incorporating the use  of
such operators.    Several   application domains  for   our  model are
discussed.\\
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TECHNICAL NOTE:  257\hfill PRICE:  \$20.00\\[0.01in]

\noindent TITLE:  RESEARCH ON NATURAL-LANGUAGE PROCESSING AT SRI\\
AUTHOR:  BARBARA J. GROSZ\\
DATE:  NOVEMBER 1981\\[0.01in]

     ABSTRACT: Research on natural-language processing at  SRI spans a
broad spectrum  of activity.  Two of our  major current efforts  are a
pair  of  research  projects  under  the sponsorship   of  the Defense
Advanced Research Projects  Agency.  The TEAM project  is intended  to
provide  natural-language access to large  databases via  systems that
are easily adaptable to a wide range of new application domains.   The
KLAUS  project is a  longer-range  effort  to  address  basic research
problems in natural-language semantics, commonsense reasoning, and the
pragmatics   of natural-language  communication.  These  two  projects
share a common core-language-processing system called DIALOGIC.\\
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\begin{tabbing}
\noindent TITLE: \= PARALLELISM IN PLANNING AND PROBLEM SOLVING:\\
         \> REASONING ABOUT RESOURCES\\
AUTHOR:  DAVID E. WILKINS\\
DATE:  JANUARY 1982\\[-0.15in]
\end{tabbing}

     ABSTRACT: The implications of allowing parallel actions in a plan
or problem  solution are discussed.   The planning system  should take
advantage of helpful  interactions between   parallel  branches,  must
detect  harmful interactions, and,  if  possible,  remedy them.   This
paper describes  what  is involved  in this   and  presents  some  new
techniques that are  implemented in an  actual planning system and are
useful in seeking solutions to these problems.  The most  important of
these  techniques,    reasoning  about resources,  is emphasized   and
explained.\\
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TECHNICAL NOTE:  259\hfill PRICE:  \$20.00\\[0.01in]

\noindent TITLE:  PLANNING NATURAL-LANGUAGE UTTERANCES TO SATISFY MULTIPLE
 GOALS\\
AUTHOR:  DOUGLAS E. APPELT\\
DATE:  MARCH 1982\\[0.01in]

     ABSTRACT: This dissertation presents the results of research on a
planning formalism for  a theory of   natural-language generation that
will support the generation of utterances that satisfy multiple goals.
Previous   research    in    the   area  of  computer   generation  of
natural-language utterances  has concentrated two  aspects of language
production: (1) the process of producing surface syntactic forms  from
an underlying representation,  and (2) the  planning of  illocutionary
acts to satisfy  the speaker's goals.  This  work concentrates on  the
interaction between   these two aspects  of  language   generation and
considers the overall problem to be one of  refining the specification
of an illocutionary act into a surface syntactic form, emphasizing the
problems of achieving multiple goals in a single utterance.

     Planning utterances requires an ability to reason in detail about
what the   hearer   knows   and wants.   A   formalism,  based  on   a
possible-worlds  semantics of  an intentional  logic  of knowledge and
action,  was used for representing the  effects  of illocutionary acts
and the speaker's  beliefs about the hearer's  knowledge of the world.
Techniques are described that  enable  a planning  system to   use the
representation effectively.

     The  language-planning theory and   knowledge  representation are
embodied in  a computer system called KAMP   (Knowledge And Modalities
Planner), which plans both physical  and  linguistic  actions, given a
high-level description of the speaker's goals.

     The  research   has  application  to  the   design  of gracefully
interacting computer systems, multiple-agent planning systems, and the
planning of knowledge acquisition.\\
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TECHNICAL NOTE:  260\hfill PRICE:  \$18.00\\[0.01in]

\noindent TITLE:  SPECIAL RELATIONS IN PROGRAM-SYNTHETIC DEDUCTION\\
AUTHORS:  ZOHAR MANNA and RICHARD WALDINGER\\
DATE:  MARCH 1982\\[0.01in]

     ABSTRACT: Program synthesis  is  the  automated   deviation  of a
computer program from    a given
specification.    In  the \underline{deductive} \underline{approach}, the
 synthesis of a program is regarded as a theorem-proving
problem; the desired  program is constructed as  a   by-product of the
proof.   This paper presents a   formal deduction  system for  program
synthesis,    with  special  features   for handling    equality,  the
equivalence connective, and ordering relations.

     In proving theorems involving the  equivalence connective, it  is
awkward to remove  all  the quantifiers  before attempting the  proof.
The system therefore deals with \underline{partially}  \underline{skolemized}
 \underline{sentences}, in
which some of  the quantifiers may be left   in  place.   A  rule   is
provided for removing individual quantifiers  when required after  the
proof is under way.

     The system is also \underline{nonclausal}; i.e., the theorem does not need
to be put into conjunctive normal form.  The equivalence, implication,
and other connectives may be left intact.\\
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\noindent TITLE:  COMPUTATIONAL STEREO\\
AUTHORS:  STEPHEN T. BARNARD and MARTIN A. FISCHLER\\
DATE:  MARCH 1982\\[0.01in]

     ABSTRACT: Perception of  depth is  a  central  problem in machine
vision.   Stereo  is an  attractive  technique  for  depth  perception
because, compared to monocular  techniques, it  leads to more  direct,
unambiguous, and  quantitative  depth measurements,  and  unlike  such
active" approaches  as radar  and laser  ranging,  it is suitable  in
almost all application domains.

We  broadly  define computational   stereo    as  the recovery  of the
three-dimensional characteristics  of   a scene  from multiple  images
taken from  different points of view.  The  first part  of   the paper
identifies and discusses each  of  the  functional components  of  the
computational stereo  paradigm:  image acquisition,   camera modeling,
feature acquisition, matching, depth determination, and interpolation.
The second  part   discusses the    criteria that are   important  for
evaluating    the    effectiveness  of  various  computational  stereo
techniques.   The third part  surveys  a  representative  sampling  of
computational stereo research.\\
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TECHNICAL NOTE:  263R\hfill PRICE:  \$10.00\\[0.01in]

\noindent TITLE:  TEAM:  A TRANSPORTABLE NATURAL-LANGUAGE INTERFACE SYSTEM\\
AUTHOR:  BARBARA J. GROSZ\\
DATE:  NOVEMBER 1982\\[0.01in]

     ABSTRACT:  A  major benefit of  using  natural language  to access the
information in a database is that it shifts onto the system  to burden
of mediating between two views of the data: the way in which the  data
is stored (the database  view''),  and the  way in  which  an end-user
thinks about it (the user's view'').  Database information is recorded
in  terms of   files, records, and    fields, while   natural-language
expressions  refer to the  same information in terms  of entities  and
relationships  in  the   world.  A major    problem in constructing  a
natural-language interface  is determining how  to encode and use  the
information    needed  to     bridge   these  two    views.    Current
natural-language  interface  systems  require  extensive  efforts   by
specialists in  natural-language processing to  provide them with  the
information they need to do the bridging.  The systems are, in effect,
handtailored to provide access to particular databases.

     This paper focuses on the problem of constructing \underline{transportable}
natural-language interfaces, i.e.,   systems that can  be adapted   to
provide access  to  databases  for which they were  not   specifically
handtailored.   It describes an  initial  version   of a transportable
system, called TEAM (for \underline{T}ransportable \underline{E}nglish
 \underline{A}ccess Data
\underline{M}anager).  The hypothesis underlying the research  described in
 this
paper is  that  the information  required  for the  adaptation  can be
obtained  through  an  interactive dialogue  with  database management
personnel  who  are   not   familiar with natural-language  processing
techniques.\\
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