INLS-210-40
– Evolving Optimal Informative Systems
Fall 2001, Fridays, 9-11:30, Room 304
UNC-CH SILS
Bob Losee, Manning 302
962-7150, losee@unc.edu
Informative systems provide more or less information of varying degrees of quality. What is an optimal informative system? How is optimality developed and determined? When does it make sense to talk about optimality? We take several perspectives that can be used in modeling describable natural (e.g., biological) and artificial (e.g. human produced) informative systems, emphasizing evolution, self-organization, and machine learning.
Losee, “Discipline Independent
Definition of Information,” http://ils.unc.edu/~losee/book5.pdf
* Dupre, The Latest on the Best, MIT Press,
1987. QH371.L38 1987
Schoemaker, “The Quest for Optimality,” Behavioral
and Brain Sciences, 14, 205-245, 1991.
Initially skim the article, the responses, and the author’s response, to
identify the key issues; then go back and read the article and responses for
details.
* Orzack and Sober, Adaptationism and Optimality,
Cambridge, 2001.
* Dennet, Darwin’s Dangerous Idea: Evolution and
the Meanings of Life, Touchstone, 1995.
* Ridley, Genome, Perennial, 1999.
+ Segerstrale, Defenders of
the Truth, Oxford, 2000. pp. 1-196 (Part I) in paperback edition, 2001.
* Sterelny, Dawkins Vs. Gould, Totem Books,
2001.
* Kaufman, At Home in the Universe, Oxford,
1995.
* Kaufman, Origins of Order, Oxford, 1993.
* Sole and Goodwin, Signs of
Life: How Complexity Pervades Biology, Basic Books, 2000.
+ Wesson, Beyond Natural
Selection, MIT 1991. Recommended Ch
1-7, Required Ch 8-13.
* Bonner, First Signals: The Evolution of
Multicellular Development, Princeton, 2000.
* Croft, Explaining
Language Change, Longman, 2000.
+ Hauser, Evolution
of Communication, MIT Press, 1996. Chapters 1, 2, 3, and 8.
Losee, “Communication Defined as Complementary
Informative Processes,” http://ils.unc.edu/~losee/ci/comminfo.pdf
+ Baldi, Bioinformatics: The
Machine Learning Approach, MIT Press, Second edition, 2001. Chapter 1 (Second edition is preferred for
this course, but chapters assigned below are the same chapter number for first
and second editions)
+ Deacon, The Symbolic
Species, Norton, 1997, Ch. 1-3.
Baldi, Chapter 2-3
Baldi, Chapters 4-6.
Baldi, Ch. 7-8
INLS 172 is recommended although not required. While there is no mathematical prerequisite, students should anticipate reading materials describing a variety of mathematical techniques consistent with a variety of mathematical paradigms. Math phobic students will be very uncomfortable in this course; students are not expected to understand everything they read, but are expected to appreciate the different approaches.
The Graduate School Handbook recommends that students not take more than 9 hours course credit if they work 10 to 20 hours a week. Students working more than 20 hours per week (but less than full time) are recommended to take only 6 hours course credit a week. Students not following these recommendations can expect to benefit from courses far less than students following these recommendations.
Each student is expected to write (and then orally present) a paper of an original 5 to 20 pages in length addressing optimality in an information system context. This is expected to be based on original ideas and/or an original analysis of data.
Class participation & Homework 60%,
Final Paper and Presentation 40%
Students should familiarize themselves with the University
of North Carolina at Chapel Hill Honor Code, which is described in University
publications. It should be noted that
in this course, students may receive (and provide) some assistance with general
problem solving techniques and the readings.
Students should NOT receive (or provide) major creative assistance on
the class project.