Subject: From: AIList Moderator Kenneth Laws <AIList-REQUEST%sri-ai.arpa@CSNET-RELAY>

From: [email-masked]
Date: Thu, 23 Jan 86 02:46:34 est

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Subject: AIList Digest   V4 #12
To: AIList%sri-ai.arpa@CSNET-RELAY
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AIList Digest           Thursday, 23 Jan 1986      Volume 4 : Issue 12

Today's Topics:
  Natural Language - Modulated Kitchens and Superior Borders,
  Humor - Pseudoscience Jargon,
  Logic & Humor - Proof that P = NP,
  Games - Othello Tournament Information
  Literature - New Text on Natural Language Processing

----------------------------------------------------------------------

Date: 22 Dec 1985 1822-PST (Sunday)
From: Steven Tepper <greep@camelot>
Subject: modulated kitchens and superior borders

>From a recent issue of the Chronicle:

        "When you mount the cooker hood on a modulated kitchen,
        please care that the superior border of the caliber is
        on the inferior border of the incorporated board.  When
        you fix the cooker hood to the incorporated board, please
        set this border on the wall up on the bottom of the
        incorporated board and use the unhooped holes."

   Instructions for fitting a stove hood made in Italy by the Zanussi
   company.  The Plain English Campaign in London has awarded the
   directions its annual prize for the worst example of bureaucratic
   language, citing an "incompetent and baffling translation from an
   unknown language into sub-English."

   [This should give the machine translation people something to
   shoot for.  -- KIL]

------------------------------

Date: Wed, 15 Jan 86 09:59 EST
From: Sonny Crockett <[email-masked]>
Subject: A good one on HAL

        I just got the videotape of 2010, and figured out what Dr. Chandra
said about the reason HAL screwed up in the first mission.  The major
problem most SF authors have is trying to come up with ways to express
advanced scientific things in a way that sounds very scientific...this
is a great one:

        (Dr. Chandra has just finished explaining that HAL was given
         conflicting orders, and was only trying to interpret them
         the best he could)
        "...HAL was trapped, more precisely he got caught in an H. Mobius
         Loop, which is possible in autonomous call-seeking computers."

I thought it was funny, anyway...

                                -Chris

PS  If anyone (like me) enjoys laughing at these kind of "pseudo-science"
    phrases, I recommend watching Dr. Who (most famous for "Multi-dimensional
    Time/Space Vortex"), and Star Trek ("Hodgkins Theory for Parallel Planet
    Development," is one of my favorites).  I'm sure there are many others
    as well.

------------------------------

Date: Fri, 27 Dec 85 16:11:46 pst
From: Alain Fournier <[email-masked]>
Reply-to: [email-masked] (Alain Fournier)
Subject: Logic & Humor - Proof that P = NP

         [Forwarded from the Stanford bboard by Laws@SRI-AI.]

> From: Len <[email-masked]>
>
> $15 to anyone who can prove P = NP.
>
> #8^)
> Len

This is an old one, but what the hell, it's $15.00:

       -----------------------------------
       |   Exactly 2 of the statements   |
       |   in these 3 boxes are false    |
       |                                 |
       -----------------------------------

       -----------------------------------
       |                                 |
       |            P != NP              |
       |                                 |
       -----------------------------------

       -----------------------------------
       |   The statement in the first    |
       |   box is true.                  |
       |                                 |
       -----------------------------------

It is left to the reader to show that assuming statement 1 is true leads
to a contradiction, so 1 is false, therefore 3 is false, and 2 has to be false.
The same conclusion is reached if the truth value of 3 is examined.
So 2 is false, and P=NP, QED.
The $15 can be sent in my name to my favourite charity, the Douglas Hofstadter
Home for the Terminally Self-Referential. An accompanying note should specify
that I requested that my gift should have no accompanying note.

------------------------------

Date: January 17, 1986,  5:51 PM.
From: <[email-masked]>
Subject: Othello Tournament Information

For anyone who might be interested in the upcoming Computer Othello
Tournament at CSU, Northridge on February 15-16:

Yoy may contact the tournament organizers over BITNET at the following
addresses --

     Brian Swift ([email-masked])
     Marc Furon  ([email-masked])

Any questions or requests for information about the tournament may be
sent to either of us at the addresses above.  We look forward to a
successful tournament and hope to hear from any and all interested Othello
programmers.

Thanks to Kurt Godden for sending the announcement to AILIST.

                                       Marc Furon

Yes, Othello is a trademark of CBS Toys.

------------------------------

Date: Tue, 14 Jan 86 09:52:55 EST
From: "Richard E. Cullingford" <[email-masked]>
Subject: new AI text

This note is an announcement of a new AI book which may be of interest
to the readers of this newsgroup. The book is "Natural Language
Processing: A Knowledge Engineering Approach," and it will be
available from Rowman & Allanheld, Publishers, of Totowa, NJ,
early in the spring of 1986. The work is intended as a practical
introduction to a theory and technology for building natural
language text-processing interfaces to database management
or expert reasoning systems. The text has been in use, in manuscript, in
courses at Princeton University and Georgia Tech for the past two years,
and extensive course materials have been developed. A software system,
the NLP Toolkit, is also available, through the publisher, that runs all
of the text's examples, and is suitable for experimentation by teachers
and programmers. The Toolkit contains representation design tools, a
conceptual analyzer, a conceptual generator, a large shared dictionary,
and a knowledge-base management support package.

Questions regarding the book and the programs can be addressed to
the author, Richard E. Cullingford, at the School of Information &
Computer Science, georgia Tech, Atlanta, GA 30332; at (404) 894-3227;
or gatech!rec (uucp) or rec@gatech (csnet). The book's table of contents
follows:

               Table Of Contents
Natural Language Processing: A Knowledge Engineering Approach

Preface
Notes on the Use of This Book
Acknowledgments
Table of Contents
Table of Diagrams
Table of Figures

Chapter 1: Natural Language Processing: An Overview

1.0 Introduction
1.1 Related Fields: An Overview
 1.1.1 NLP, Artificial Intelligence, and Knowledge Engineering
 1.1.2 NLP and the Sciences of Language
1.2 NLP Efforts in AI
 1.2.1 Early Efforts
 1.2.2 Second Generation Systems
 1.2.3 Third Generation Systems: A Look into the Future
1.3 Outline of the Book

Part I: A General-Purpose Language Processing Interface

Chapter 2: An Introduction to Representation Design

2.0 The Representation Problem
2.1 The Need for a Formal Representational System
2.2 Requirements on a Representational System
2.3 Introduction to ERKS
        2.3.1 The ISA-Hierarchy of the Core System
        2.3.2 Criteria for Selection of the Primitive Types
2.4 ERKS in LISP
2.5 The Maximal Inference-Free Paraphrase
2.6 Building a Model Corpus
2.7 A Simple Corpus
2.8 Primitive Actionals and Statives
2.9 Conceptual Relationships
2.10 A Representational Case Study: CADHELP
        2.10.1 The CADHELP Microworld
        2.10.2 A Typical Command
        2.10.3 Knowledge Representation Issues
2.11 Summary

Chapter 3: Software Tools for Representation Design

3.0 Introduction
3.1 Navigating in an ISA-Hierarchy
3.2 Defining ERKS Types
3.3 Access and Updating Machinery
3.4 The def-wordsense Record Macro
3.5 Summary

Chapter 4: Surface-Semantic Conceptual Analysis

4.0 Introduction: Lexicon-Driven Analysis
4.1 A Simple Model of Sentence Structure
4.2 Production Systems, Requests, and Processing Overview
4.3 Request Pool Consideration
   4.3.1 Analysis Environment
   4.3.2 Request Types
4.4 Requests in More Detail
4.5 Morphological Fragments and "to be"
4.6 A Processing Example
4.7 Summary

Chapter 5: Problems in Conceptual Analysis

5.0 Introduction
5.1 Tri-Constituent Forms and Imbedded Sentences
        5.1.1 Handling Indirect Objects
        5.1.2 Infinitives and Gerunds
        5.1.3 Relative Clauses
5.2 Prepositions and "to be," Revisited
5.3 Word Meaning Disambiguation
        5.3.1 Pronominal Reference
5.4 Coordinate Constructions
5.5 Ellipsis Expansion
5.6 A Concluding Example
5.7 Summary

Chapter 6: Generating Natural Language from a Conceptual Base

6.0 Introduction
6.1 Overview of Generation Process
6.2 Dictionary Entries
6.3 Morphology and the Verb Kernel
   6.3.1 Plural and Possessive Morphology
   6.3.2 Subject-Verb Agreement and Modals
   6.3.3 Tensing
   6.3.4 Subject-Auxiliary Inversion
6.4 "Advanced" English Syntax
   6.4.1 The Infinitive Construction
   6.4.2 The Possessive Sketchifier
   6.4.3 The Entity-Reference Sketchifier
6.5 A Processing Example
6.6 Summary

Part II: Building a Conversationalist

Chapter 7: Summarizing Knowledge Bases

7.0 Introduction: What to Say versus How to Say It
7.1 Explanations as Summaries
7.2 Explanations in CADHELP
7.3 Representational Overview
7.4 Concept Selection
7.5 An Example
7.6 Summary

Chapter 8: Knowledge-Base Management

8.0 Introduction
8.1 KB Organization
   8.1.1 The Slot-Filler Tree
   8.1.2 Slot-Filler Tree Construction
   8.1.3 Index Quality
   8.1.4 Best-First Ordering of KB Items
8.2 KB Search
   8.2.1 The Tree Search Mechanism
8.3 Performance
8.4 Summary

Chapter 9: Commonsense Reasoning

9.0 Introduction: The Need for Reasoning in Language Understanding
9.1 Deductive Retrieval
9.2 YADR, Yet Another Deductive Retriever
9.3 The YADR Interface
9.4 The YADR Top Level
9.5 Logical Connectives in Antecedent Forms
9.6 Summary

Chapter 10: Putting It All Together: A Goal-Directed Conversationalist

10.0 Introduction
10.1 The ACE Microworld
10.2 A Model of Purposive Conversation
10.3 The Conversational Strategist
10.4 The Conversational Tactician
10.5 The Academic Scheduling Expert
10.6 More Problems in Language Understanding
    10.6.1 Coordinate Constructions and Ellipses
    10.6.2 Defining "And" for the Analyzer
    10.6.3 Using Expectations during Analysis
10.7 More Problems in Language Generation
    10.7.1 Asking Questions
    10.7.2 Producing Coordinate Constructions
    10.7.3 Generating Attributes, Absolute Times, Locales, and Names
10.8 Putting It All Together: A Session with ACE
10.9 Parting Words

Appendix I: The ERKS Types
Appendix II: Source for YADR, Yet Another Deductive Retriever
Appendix III: Glossary of Terms

                        Rich Cullingford

------------------------------

End of AIList Digest
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