bobgian@psuvax.UUCP (01/02/84)
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* Spring Term Artificial Intelligence Seminar Syllabus *
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MODELS OF SENTIENCE
Learning, Cognitive Model Formation, Insight, Discovery, Expression;
"Subcognition as Computation", "Cognition as Subcomputation";
Physical, Cultural, and Intellectual Evolution.
SYMBOLIC INPUT CHANNELS: PERCEPTION
Vision, hearing, signal processing, the "signal/symbol interface".
SYMBOLIC PROCESSING: COGNITION
Language, Understanding, Goals, Knowledge, Reasoning.
SYMBOLIC OUTPUT CHANNELS: EXPRESSION
Motor skills, Artistic and Musical Creativity, Story Creation,
Prose, Poetry, Persuasion, Beauty.
CONSEQUENCES OF THESE MODELS
Physical Symbol Systems and Godel's Incompleteness Theorems;
The "Aha!!!" Phenomenon, Divine Inspiration, Extra-Sensory Perception,
The Conscious/Unconscious Mind, The "Right-Brain/Left-Brain" Dichotomy;
"Who Am I?", "On Having No Head"; The Nature and Texture of Reality;
The Nature and Role of Humor; The Direct Experience of the Mystical.
TECHNIQUES FOR DEVELOPING THESE ABILITIES IN HUMANS
Meditation, Musical and Artistic Experience, Problem Solving,
Games, Yoga, Zen, Haiku, Koans, "Calculus for Peak Experiences".
TECHNIQUES FOR DEVELOPING THESE ABILITIES IN MACHINES
REVIEW OF LISP PROGRAMMING AND FORMAL SYMBOL MANIPULATION:
Construction and access of symbolic expressions, Evaluation and
Quotation, Predicates, Function definition; Functional arguments
and returned values; Binding strategies -- Local versus Global,
Dynamic versus Lexical, Shallow versus Deep; Compilation of LISP.
IMPLEMENTATION OF LISP: Storage Mapping and the Free List;
The representation of Data: Typed Pointers, Dynamic Allocation;
Symbols and the Symbol Table (Obarray); Garbage Collection
(Sequential and Concurrent algorithms).
REPRESENTATION OF PROCEDURE: Meta-circular definition of the
evaluation process.
"VALUES" AND THE OBJECT-ORIENTED VIEW OF PROGRAMMING: Data-Driven
Programming, Message-Passing, Information Hiding; the MIT Lisp Machine
"Flavor" system; Functional and Object-Oriented systems -- comparison
with SMALLTALK.
SPECIALIZED AI PROGRAMMING TECHNIQUES: Frames and other Knowledge
Representation Languages, Discrimination Nets, Augmented Transition
Networks; Pattern-Directed Inference Systems, Agendas, Chronological
Backtracking, Dependency-Directed Backtracking, Data Dependencies,
Non-Monotonic Logic, and Truth-Maintenance Systems.
LISP AS THE "SYSTEMS SUBSTRATE" FOR HIGHER LEVEL ABSTRACTIONS:
Frames and other Knowledge Representation Languages, Discrimination
Nets, "Higher" High-Level Languages: PLANNER, CONNIVER, PROLOG.
SCIENTIFIC AND ETHICAL CONSEQUENCES OF THESE ABILITIES IN HUMANS
AND IN MACHINES
The Search for Extra-Terrestrial Intelligence.
(Would we recognize it if we found it? Would they recognize us?)
The Search for Terrestrial Intelligence.
Are We Unique? Are we worth saving? Can we save ourselves?
Why are we here? Why is ANYTHING here? WHAT is here?
Where ARE we? ARE we? Is ANYTHING?
These topics form a cluster of related ideas which we will pursue more-or-
less concurrently; the listing is not meant to imply a particular sequence.
Various course members have expressed interest in the following software
engineering projects. These (and possibly others yet to be suggested)
will run concurrently throughout the course:
LISP Implementations:
For CMS, in PL/I and/or FORTRAN
In PASCAL, optimized for personal computers (esp HP 9816)
In Assembly, optimized for Z80 and MC68000
In 370 BAL, modifications of LISP 1.5
New "High-Level" Systems Languages:
Flavor System (based on the MIT Zetalisp system)
Prolog Interpreter (plus compiler?)
Full Programming Environment (Enhancements to LISP):
Compiler, Editor, Workspace Manager, File System, Debug Tools
Architectures and Languages for Parallel {Sub-}Cognition:
Software and Hardware Alternatives to the Von-Neuman Computer
Concurrent Processing and Message Passing systems
Machine Learning and Discovery Systems:
Representation Language for Machine Learning
Strategy Learning for various Games (GO, CHECKERS, CHESS, BACKGAMMON)
Perception and Motor Control Systems:
Vision (implementations of David Marr's theories)
Robotic Welder control system
Creativity Systems:
Poetry Generators (Haiku)
Short-Story Generators
Expert Systems (traditional topic, but including novel features):
Euclidean Plane Geometry Teaching and Theorem-Proving system
Welding Advisor
Meteorological Analysis Teaching system
READINGS -- the following books will be very helpful:
1. ARTIFICIAL INTELLIGENCE, Patrick H. Winston; Addison Wesley, 1984.
2. THE HANDBOOK OF ARTIFICIAL INTELLIGENCE, Avron Barr, Paul Cohen, and
Edward Feigenbaum; William Kaufman Press, 1981 and 1982. Vols 1, 2, 3.
3. MACHINE LEARNING, Michalski, Carbonell, and Mitchell; Tioga, 1983.
4. GODEL, ESCHER, BACH: AN ETERNAL GOLDEN BRAID, Douglas R. Hofstadter;
Basic Books, 1979.
5. THE MIND'S I, Douglas R. Hofstadter and Daniel C. Dennett;
Basic Books, 1981.
6. LISP, Patrick Winston and Berthold K. P. Horn; Addison Wesley, 1981.
7. ANATOMY OF LISP, John Allen; McGraw-Hill, 1978.
8. ARTIFICIAL INTELLIGENCE PROGRAMMING, Eugene Charniak, Christopher K.
Riesbeck, and Drew V. McDermott; Lawrence Erlbaum Associates, 1980.
--
Bob Giansiracusa (Dept of Computer Science, Penn State Univ, 814-865-9507)
Arpa: bobgian%psuvax1.bitnet@Berkeley Bitnet: bobgian@PSUVAX1.BITNET
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