The Theme: Simulation

In 2001, (then-)Yale lecturer Nick Bostrom rocked the philosophy world by arguing that we are all probably (not just possibly) characters in the simulation of some superior being.  If this is the case, it has unsettling implications even for those who do not usually trouble themselves with metaphysical skepticism.  What if our sim-user decides to turn off the computer?  Moreover, what does this imply about the relationship between our lives and "true" reality?  What are the consequences of "living in sim"?

Bostrom's paper has met with its own skepticism, about the soundness of his arguments.  But whether we take the simulation argument seriously or not, the relationship between simulation and reality is deeply puzzling.  Simulation is, almost by definition, designed to fool us.  Yet, increasingly, we enter simulated worlds willingly.  What is it that we experience or learn from these simulations?  To what extent can we reliably map what we learn from simulation onto reality, and how can we tell the difference between simulations that are "realistic" and ones that are not? 

In systems science, simulation is a method, which we usually think of as involving computers.  It generally starts with the creation of a computer model, and a program for evolving it.  Computers are involved when the model is too complex to compute analytically (i.e. to prove theorems about), and "simulation" is usually distinguished from formal modeling on this basis.  But computational and formal modeling share the property of claiming a relationship between realilty and the structural/functional relationships between variables.  In that sense, both could be said to be a form of simulation.  Formal models have provable properties, while computational ones, by definition, do not.  Much is often made of this distinction, but we will question its importance.  Computational models are often more complicated than formal ones, and much is often made of that too, on the argument that a complicated model of complicated phenomena is more likely to be right than ais one that is simple enough to "solve" analytically.  We will question this too.  Any type of mathematically-based modeling (formal or computational) is bound to result in simplifying assumptions and willful unfaithfulness to the truth.  The modelers usually want to claim that their models are faithful enough.  How do we decide that?

Simulation is also a theme that runs through much of contemporay life, from computing applications (games, humanoid robots, user models, flight simulators, scientific modeling, virtual reality, etc.), to the humanities  (fiction versus reality, mediated versus "real" experience, theoretical versus experiential understanding) to everyday life (role playing, dreaming, remembering, and fantasy baseball camps).  A major purpose of the course is to expose just how many puzzling questions can be seen as questions about how much we can trust some form of simulation, including models we have in our minds about what other people are like and about what they (or we!) are likely to do in the future.

Simulation, then, befits the course as a topic in systems science, because it is a very general concept, because simulation is perhaps the defining method of systems thinking, and because a simulation can be mapped onto anything that shares its structure, even though the new target of application may appear to come from a completely different domain from what inspired the simulation.

Course Overview:

In systems science, the simulation-based work that has received the most attention in recent years has been Stephen Wolfram's A New Kind of Science (2002).  The plan I propose for the quarter is to spend the first half of the term working through much of Wolfram's book, which is available free in electronic form online (at http://www.wolframscience.com/nksonline/toc.html).  Then, for the last five weeks of the quarter, I propose that we devote each week to a different disciplinary perspective on simulation: physical and biological science, cognitive science/AI, social science, philosophy/humanities, and education.  During the last half of the course, discussions will, I propose, be student-led, with the readings partly reflecting the interests of students who lead discussions each week.   Students will be expected to do more reading for the topics they present than is expected of the whole class on that topic. 

The requirements for the course are that each student (a) lead a discussion, (b) write a paper based on the material they present, and (c) write two commentaries based on material presented by other students.  If everyone agrees, I will post papers and commentaries on this website so that they can be read by all.  Guidelines for the papers/commentaries may be found here.

Tentative Schedule:

Week 1 (March 29).  Introductions and overview. 

Week 2 (April 5).  Meeting by Internet (details to be announced). Groundwork chapters for A New Kind of Science.
Reading: Wolfram, chapters 1-4

Week 3 (April 12).  "Mechanisms in Programs and Nature" and "Implications for Everyday Systems".
Reading: Wolfram, chapters 7-8

Week 4 (April 19). "Processes of Perception and Analysis" and "The Notion of Computation".
Reading: Wolfram, chapters 10-11
                    >> Greg Wayne, Commentary on Wolfram chapter 10

Week 5 (April 26). "The Principle of Computational Equivalence".
Reading: Wolfram, chapter 12
                Pick any two reviews from W. Edwin Clark's page of NKS reviews.

Week 6 (May 3). Perspectives from physical and evolutionary science.
Reading: Stainforth, D.A., et al. (2005). Uncertainty in predictions of the climate response to rising levels of greenhouse gasses. Nature, 433:403-407 with more info at climateprediction.net
               Nowak, M. A., Komarova, N., & Niyogi, P. (2001). Evolution of universal grammar.  Science 291, 114-118. 
                Pinker, S. (2003). Language as an adaptation to the cognitive niche. In Christanen, M.H. and Kirby, S. (Eds.), Language Evolution. New York: Oxford University Press,  pp.  21-37
                Kauffman, S. (1995). At Home in the Universe: The Search for Laws of Self-Organization and Complexity. New York: Oxford University Press, pp. 51-66.
                   >> Katarina Ling, Review of Kaufman
Student Presenters: Mike LeBeau and Katarina Ling

Week 7 (May 10). Perspectives from cognitive science and artificial intelligence.
Reading: Simon, H.A. (1981). Sciences of the Artificial (Second edition), excerpts
                 >> Brendan O'Connor, Review of Simon
               Newell, A. (1973).  You can't play 20 questions with nature and win: Projective comments on the papers of this symposium.  In W.G. Chase (Ed.), Visual Information Processing. New York: Academic Press, pp. 283-308.
               Sloman, A. (2002). Architecture-based conceptions of mind. In Gardenfors, P., Kijania-Placek, K., & Wolenski, J. (Eds.), In the Scope of Logic, Methodology, and Philosophy of Science (Vol. II). Dordrecht: Kluwer, pp. 403-427.
                   >> Kem Ozbek, Review of A. Sloman
               Langley, P., & Rogers, S. (2005). Cumulative learning of hierarchical skills from problem solving and execution, Technical Report, Institute for the Study of Learning and Expertise, Palo Alto, California.
                   >> Ben de Jesus, Review of Icarus
Recommended: Sloman, S. Cognitive architectures, MIT CogNET
Student Presenters: Kem Ozbek, Ben de Jesus, and Darryl Reeves
                   >> Darryl Reeves, Review of Simon and of Newell
                    >> Jon Shih, Commentary on Week 7
                            
Week 8 (May 17). Perspectives from social science.
Reading:  Axelrod, R. (2003). Advancing the art of simulation in the social sciences. Japanese Journal for Management Information Systems.
                   >> Dylan Marks, Review of Axelrod
                   >> Scott Lanum, Commentary on Axelrod
                 Rauch, J. (2002). Seeing around corners,  Atlantic Monthly, April.
                   >> Darryl Reeves, Commentary on Rauch
                 Bailenson, J.N., Beall, A.C., Loomis, J., Blascovich, J., & Turk, M. (2004). Transformed social interaction: Decoupling representation from behavior and form in collaborative virtual environments. PRESENCE: Teleoperators and Virtual Environments, 13(4), 428-441.
                   >> Jon Shih, Review of Bailenson et al.
                   >> Katarina Ling, Hesitations about Transformed Social Interaction (Commentary)
Student Presenters: Brendan O'Connor, Jon Shih, and Dylan Marks
                    >> Brendan O'Connor, Simulation versus analytic methods
Week 9 (May 24). Perspectives from philosophy and the humanities.
Reading: Baudrillard, J. (1991). Simulacra and science fiction.  Science Fiction Studies, 18(3).
                   >> Greg Wayne, Review of Baudrillard
                   >> Kem Ozbek, Commentary on Week 9
                Benjamin, W. (1936). The work of art in the age of mechanical reproduction.
                   >> Dylan Marks, Commentary on Simulation of Art
                Lessig, L. (2004). Transformers, Free Culture. Penguin, chapter 8, pp. 100-107
                   >> Scott Lanum, Commentary on Lessig
                Bostrom, N. (2001). Are you living in a computer simulation?
                    >> Brian Eggleston, Review of Bostrom
Student Presenters: Greg Wayne and Brian Eggleston

Week 10 (May 31). Perspectives from education.
Games: SimCity 4
Reading: Squire, K. (2003). Video games in education. International Journal of Intelligent Simulations and Gaming, 2(1).
                   >> Jon Shih, Commentary on Squire
               Widdison, R., Aikenhead, M., & Allen, T. (1998). Simulation in legal education. 13th Annual BILETA Conference: "The Changing Jurisdiction", Dublin, March 27-28.
               Groupman, J. (2005). A model patient: Howsimulators are changing the way doctors are trained. The New Yorker, 81(May 2): 48-54.
                   >> Scott Lanum, Review of Groopman
               Parker, S.T. (1984).  Playing for keeps: An evolutionary perspective on human games. In Smith, P.K. (Ed.), Play in Animals and Humans, pp. 271-294.
                   >> Tony Tulathimutte, Review of Parker
                   >> Greg Wayne, Commentary on Parker
Student Presenters: Tony Tulathimutte, Scott Lanum, and Michelle Lee
                   >> Katarina Ling, Value of Unwinnable Games (Commentary)
                   >> Brian Eggleston, Commentary and Education and Entertainment
                   >> Dylan Marks, Commentary and Simulation and Education
                   >> Ben de Jesus, Commentary on Simulations and Games

Film Series: "Simulation and Its Discontents"

We will be showing films after class, beginning at 9:15, in the course classroom (160-314).  These films have been chosen by students and the instructor to go with the theme of the course and are open to people who are not taking the course.  The scheduled films are:

April 26  - Pi (1998, 84 mins.)
                                                                               
May 3 - Primer (2004, 78 mins.)
                                                                               
May 10  -  The Stepford Wives (1975, 115 mins.)
                                                                               
May 17 - Quiet Rage: The Stanford Prison Study (1988, 52 mins.) and
                Obedience (1965, 40 mins.)
                                                                               
May 24 - Zelig (1983, 79 mins.)
                                                                               
May 31 - Black Like Me (1964, 107 mins.)