I400/I590 Artificial Life as an approach to Artificial
Intelligence
Spring Semester 2007
Professor: Larry Yaeger
Office: Eigenmann Hall, Rm 907 (South wing)
Office Hours: By appointment, any afternoon or early evening I'm not in a class or meeting; see my work calendar
Phone: (812) 856-1845
Email: larryy (at) indiana.edu
Meeting Times: 2:30pm – 3:45pm MW Location: Informatics Bldg, Rm I107
Textbook (required): Braitenberg, V. Vehicles: Experiments in Synthetic Psychology
All other reading materials available online via links on this page (on the private site only).
NOTE: This document
appears in both a public and a private place; reading material links
only work on the private site, to abide by
copyright restrictions. (Lecture
note links work on both sites.)
The private siteÕs URL is provided to enrolled students and is
accessible via OnCourse.
Schedule and Reading List
Links under the ÒTopicsÓ heading are to PowerPoint lecture notes. You can download these in advance if you want something to take notes on, but be warned, they are likely to be in flux until the day of the class.
In the topics, S# means Speaker #. (Speaker topics can be inferred from the schedule, but are listed explicitly at the bottom of this page.)
In the reading assignments, B# means chapter # of the Braitenberg book.
L# is Lecture #.
|
Class |
Date |
Topics |
Reading Assignment (for next class) |
Extras (not required) |
|
1a |
MO 8 Jan |
Class intro, L1-Intro to Artificial Life |
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1b |
WE
10 Jan |
Intro to Braitenberg, L2-Is it alive? |
Farmer & Belin, B1 |
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MO
15 Jan |
No class - MLK Holiday |
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2b |
WE
17 Jan |
S1 (WillP), B1, L3-Intro to GAs |
Goldberg, B2 |
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3a |
MO
22 Jan |
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3b |
WE
24 Jan |
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4a |
MO
29 Jan |
Exam 1, take-home |
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4b |
WE
31 Feb |
Exam 1 due, L5-Neural Networks Pt. 1 - Terms & Defs |
Anderson, B4 |
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5a |
MO 5 Feb |
Return exams, S4 (JoshuaM), B4, discussion |
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5b |
WE 7 Feb |
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6a |
MO
12 Feb |
S5 (NateS, StephenD), Mitja Hmeljack on Second Life, discussion |
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6b |
WE
14 Feb |
Schneider, B6 |
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7a |
MO
19 Feb |
John Beggs guest lecture |
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7b |
WE
21 Feb |
L8-Neural Nets Pt 3 – Hebbian learning via Information Theory |
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8a |
MO
26 Feb |
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8b |
WE
28 Feb |
In-class Midterm (Exam 2) |
B8 |
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9a |
MO 5 Mar |
Return and discuss exams, S8 (no one), B8, discussion |
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9b |
WE 7 Mar |
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MO
12 Mar |
No Class - Spring Break |
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WE
14 Mar |
No Class - Spring Break |
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10a |
MO
19 Mar |
Informal presentation of project ideas |
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10b |
WE
21 Mar |
Hinton&Nowlan, Parisi, Chalmers, B9 |
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11a |
MO
26 Mar |
Olaf Sporns guest lecture |
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11b |
WE
28 Mar |
L11-Organisms simulated and real (Koko, Dolphin, Betty, Alex) |
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12a |
MO 2 Apr |
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12b |
WE 4 Apr |
Hillis, B11 |
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13a |
MO 9 Apr |
S11 (OliverM, DrewH), B11, discussion, test prep |
Exam 3, take-home |
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13b |
WE
11 Apr |
Exam 3 due, L13-Evolution of Intelligence (movies) |
Yaeger, B12 |
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14a |
MO
16 Apr |
Return exams, S12 (no one), B12, discussion |
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14b |
WE
18 Apr |
Langton2, B13, B14 |
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15a |
MO
23 Apr |
Projects due, S13 (MikeR), B13, B14, Project Demos |
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15b |
WE
25 Apr |
Project Demos, Discussion and review for final exam |
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MO
30 Apr |
Final Exam 2:45pm - 4:45pm (Exam 4) |
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Requirements
Students will be expected to attend class, do weekly readings, and participate in discussions. In addition, each student will present and lead a discussion on the material in one topic area, and will do one of the following:
á Write a final paper (grads 20-25 pages, undergrads 15-20 pages) demonstrating insight into one of the topic areas.
á Write a functioning ALife simulator of at least modest complexity (more than just a simple CA or Conway Game of Life; student should consult with teacher before writing).
á Turn in a technical paper describing the results of an ALife experiment, carried out with Tierra, Avida, Swarm, PolyWorld, or other ALife software (student may consult with teacher in selection of software and topic).
There will be four exams—two take-home exams, an in-class midterm, and an in-class final exam. The lowest test grade will be dropped, thus the final is optional, if a student is satisfied with the first three test results. The midterm and particularly the final may include cumulative questions, but will primarily focus on the material since the last test. Dates are indicated in the schedule above.
Course Structure
Generally, each weekÕs theme will bridge weekends, being introduced by me in the WE lecture class, and then followed up with readings before the next class on MO, in order to allow students maximum time to read and prepare for discussion. On the following MO, student presentations of a topic related to the reading materials will take place, followed by a discussion of one of the chapters from the Braitenberg book, followed by any additional material I need to communicate, and class discussion of that weekÕs topic. (There will be exceptions to this pattern, as indicated in the above schedule, at the start of the semester and around Spring Break.)
Each student will prepare one presentation during the semester on a topic related to the reading materials. We will agree on and set dates in the first class. If there are more than 13 students in the class, we will fit extra presentations in as needed. These presentations are to be 15 to 20 minutes only. In general, I hope students will select one of the papers referenced by the primary reading material and use that as the basis for their presentation. But if there is a topic of particular interest to a student in the reading material itself and I have not covered that topic in the lecture class, that will be acceptable. Related papers not taken from the reference list may also be acceptable, but require my approval.
Each student will also work on one final project. As indicated above, this project may take the form of writing your own ALife simulator, performing experiments with an existing ALife simulator, or researching and writing on a topic in the field, in order to accommodate all computer skill levels. Projects will be due on Monday 25 April, 2005.
Grading
Each of the four tests, class participation, the topic presentation, and the final project will contribute to the total grade as follows:
|
Participation |
5 pts |
(Yes, it really does count) |
|
Gedanken experiment |
5 pts |
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Presentation |
10 pts |
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Project |
20 pts |
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Test 1 (take-home) |
20 pts |
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Test 2 - Midterm |
20 pts |
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Test 3 (take-home) |
20 pts |
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Test 4 - Final |
20 pts |
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Total |
120 pts |
(100 pts after dropping the lowest test score) |
The extended gedanken experiment will be defined in the first week. This experiment will pose a challenge that, if answered correctly by anyone in the class, anytime before the end of the semester, will result in the credit being received by the entire class.
Grades will not be curved and will be assigned as follows (this is the same as used in I101 and I210, but differs from some other classes):
|
A+ |
98-100 |
4.0 |
|
A |
93-97 |
4.0 |
|
A- |
90-92 |
3.7 |
|
B+ |
85-89 |
3.3 |
|
B |
80-84 |
3.0 |
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B- |
75-79 |
2.7 |
|
C+ |
70-74 |
2.3 |
|
C |
65-69 |
2.0 |
|
C- |
60-64 |
1.7 |
|
D+ |
55-59 |
1.3 |
|
D |
50-54 |
1.0 |
|
D- |
45-49 |
0.7 |
|
F |
0-44 |
0.0 |
Conduct
Cooperation on the extra credit problem is encouraged, as is discussion in general. In fact, I intend to set up an email list to facilitate discussions outside of class. However, tests must be taken individually, both take-home and in-class. Cheating will be reported according to university policies.
General Course Description
Artificial Life is a broad discipline encompassing the origins, modeling, and synthesis of natural and artificial living entities and systems. Artificial Intelligence, as a discipline, tries to model and understand intelligent systems and behavior, typically at the human level. This class will introduce core concepts and technologies employed in Artificial Life systems that can be used to approach the evolution of Artificial Intelligence in computers. Key themes include:
- bottom-up design and synthesis principles,
- definitions and measurements of life and intelligence,
- genetic algorithms,
- neural networks,
- the evolution of learning,
- the emergence of intelligence,
- computational ecologies, and
- information theory-based measures of complexity.
Our path through these materials will lay the theoretical groundwork for an approach to Artificial Intelligence based on the tenets and practices of Artificial Life—an approach which utilizes evolution to start small and work our way up a spectrum of intelligence, from the simplest organisms to the most complex, rather than attempting to model human-level intelligence from the outset.
Lectures and readings will be based on seminal papers and introductory texts in these fields, drawing from the Artificial Life conference proceedings, and technical papers by Donald Hebb (from which we obtain Hebbian learning), Rumelhart and McClelland (editors of and authors in the original Parallel Distributed Processing books that launched the modern neural network field), Ralph Linsker ("Infomax" theoretical approach to neural network learning), Hinton and Nowland (the "Baldwin effect"), William James ("the greatest American psychologist"), W. Grey Walter, Tom Ray, Karl Sims, Danny Hillis, and others. We will also read and discuss Braitenberg's seductive and influential Vehicles book.
References
Anderson, J. A., General Introduction, p. xiii-xxi, Neurcomputing, Foundations of Research, ed. by J. A. Anderson and E. Rosenfeld, A Bradford Book, MIT Press, Cambridge, Massachusetts, 1988
Chalmers, D., "The Evolution of Learning: An Experiment in Genetic Connectionism" in Connectionist Models, Proceedings of the 1990 Summer School, edited by D. S. Touretzky, J. L. Elman, T. J. Sejnowski, G. E. Hinton, Morgan Kaufmann, San Mateo, CA, 1991
Douglas, F., ÒDo fruit flies dream of electric bananas?Ó, New Scientist, 14 February 2004
Farmer, J. D., and A. dÕA. Belin, "Artificial Life: The Coming Evolution" In Artificial Life II, edited by C. Langton, C. Taylor, J. Farmer, and S. Rasmussen. Proceedings of the Artificial Life II Conference (in 1990), Santa Fe Institute Studies in the Sciences of Complexity Proc. Vol. X. Addison-Wesley, Redwood City, CA, 1992
Frye, M.A. & Dickinson, M.H. ÒA signature of salience in the Drosophila brainÓ, commentary on article by Swinderen & Greenspan, Nat. Neur. 6 (6) 544-546 June 2003
Giurfa, M., Zhang, S., Jenett, A., Menzel, R., Mandyam, V., ÒThe concepts of 'sameness' and 'difference' in an insectÓ, Nature 410(6831) 930-933, 19 Apr 2001
Goldberg, D. E., A Gentle Introduction to Genetic Algorithms, p. 1-23, Chapter 1 of Genetic Algorithms in Search, Optimization, and Machine Learning, by D. E. Goldberg, Addison-Wesley 1989
Hebb, D. O., Introduction (p. xi-xix) and Chapter 4, "The first stage of perception: growth of the assembly" (p. 60-78), The Organization of Behavior, Wiley, New York, 1949 (with introduction, p. 43-56 from Neurocomputing, Foundations of Research, ed. by J. A. Anderson and E. Rosenfeld, A Bradford Book, MIT Press, Cambridge, Massachusetts, 1988)
Hillis, D. W., Intelligence as an Emergent Behavior, p. 175-189, Daedalus, Journal of the American Academy of Arts and Sciences, special issue on Artificial Intelligence, Winter 1988
Hinton, G. E. and Nowlan, S. J., How learning can guide evolution. Complex Systems, 1:495--502, 1987
Izhikevich, Eugene M., Simple Model of Spiking Neurons, IEEE Transactions on Neural Networks (2003) 14:1569-1572
http://www.nsi.edu/users/izhikevich/publications/spikes.htm
Izhikevich, Eugene M., Which Model to Use for Cortical Spiking Neurons? IEEE Transactions on Neural Networks (2004) 15:1063-1070
http://www.nsi.edu/users/izhikevich/publications/whichmod.htm
Izhikevich, Eugene M., Polychronization: Computation With Spikes, Neural Computation (2006) 18:245-28
http://www.nsi.edu/users/izhikevich/publications/spnet.htm
James, W., Association, Chapter XVI of Psychology (Briefer Course), p. 253-279, Holt, New York, 1890 (with introduction, p. 1-14 from Neurocomputing, Foundations of Research, ed. by J. A. Anderson and E. Rosenfeld, A Bradford Book, MIT Press, Cambridge, Massachusetts, 1988)
Langton, C. G., Artificial Life, preface to Artificial Life, The Proceedings of an Interdisciplinary Workshop on the Synthesis and Simulation of Living Systems held September, 1987 in Los Alamos, New Mexico, Santa Fe Institute Studies in the Sciences of Complexity Proc. Vol. VI., edited by C. Langton, Addison Wesley, Redwood City, CA, 1989
Langton, C. G., Computation at the Edge of Chaos: Phase Transitions and Emergent Computation, p. 12-37, Emergent Computation, Proceedings of the Ninth Annual International Conference of the Center for Nonlinear Studies on Self-organizing, Collective, and Cooperative Phenomena in Natural and Artificial Computing Networks, Los Alamos, NM, 1989, ed. Stephanie Forrest, North Holland, 1990
Linsker, R., "Towards an Organizing Principle for a Layered Perceptual Network" in Neural Information Processing Systems, ed. by D. Z. Anderson. American Institute of Physics, New York, 1988
Linsker, R., "Self-Organization in a Perceptual Network", Computer 21(3), 105-117, March 1988
Parisi, D., S. Nolfi, and F. Cecconi, "Learning, Behavior, and Evolution", Tech. Rep. PCIA-91-14, Dept. of Cognitive Processes and Artificial Intelligence, Institute of Psychology, C.N.R., Rome, June 1991. (Appeared in Proceedings of ECAL-91—First European Conference on Artificial Life, December 1991, Paris; also in Varela, F, Bourgine, P. Toward a pratice of autonomous systems. MIT Press. 1991
Ray, T. S. 1992. Evolution, ecology and optimization of digital organisms. Santa Fe Institute working paper 92-08-042
Rumelhart, D. E. and McClelland, J. L., PDP Models and General Issues of Cognitive Science, p. 110-146, Chapter 4 of Parallel Distributed Processing, Explorations in the Microstructure of Cognition, Volume 1: Foundations, ed. by D. E. Rumelhart, J. L. McClelland, and the PDP Research Group, A Bradford Book, MIT Press, Cambridge, Massachusetts, 1986
Schneider, T., ÒInformation Theory PrimerÓ, <http://www.lecb.ncifcrf.gov/~toms/paper/primer/>
Sims, K., Evolving Virtual Creatures, Computer Graphics, Annual Conference Series, (SIGGRAPH Ô94 Proceedings), July 1994, pp.15-22.
Walter, W. G. (1950), "An Imitation of Life", Scientific American, 182(5), 42-45, May 1950
Yaeger, L. S., Computational Genetics, Physiology, Metabolism, Neural Systems, Learning, Vision, and Behavior or PolyWorld: Life in a New Context, p. 263-298, Proceedings of the Artificial Life III Conference (in 1992), ed. Chris Langton, Addison-Wesley, 1994
Speaker Topics
S1 – Intro to Artificial Life or Is It Alive?
S2 – Genetic Algorithms
S3 – Simulated Evolution
S4 – Neural Networks, Intro
S5 – Neural Networks, Association & Hebb
S6 – Information Theory
S7 – Neural Networks, Information theoretic approach to neural network learning
S8 – Any of the above!
S9 – Combining evolution and learning
S10 – Animal intelligence, intelligence in simulated organisms
S11 – Intelligence as an emergent phenomenon
S12 – Evolution of intelligence
S13 – Complexity
Links to previous student presentations may be found on the following class home pages from previous semesters. Click on the student's name in parentheses to download the presentation. If the "S#" indicator is also a link, then it will point to supporting materials for the presentation. (Other links on these pages do not work.)
Look here for examples of previous semester projects.