Computer Science and Biology 361
Submitted by PaulGrobstein on Thu, 2006-01-26 09:01
I have no interest in defending Wolfram
as either a person or an academic scholar against the kinds of criticisms expressed (appropriately I think) in class today
. I do though want to explain and justify my characterization of his work as "digital determinism" and as a unique/important "coherent and comprehensive explanation of everything". And hence as, whatever its shortcomings, a body of exploration/thinking that it is important to understand and pay attention to.
I earlier argued
that "computer models are not capable of nor aimed at determining what is 'real'" but instead are intended "to establish that some pattern/phenomenon that is presumed to depend on complexity/planning/a directive element can be produced without that. To show what might be, rather than what is." Wolfram's work needs to be appreciated in these terms. It is an assertion that one might in principle account for all known phenomena (literally ALL, from physics through biology, psychology, sociology, history, and, yes, art) in terms of very simple things (locations having only two possible states) interacting in very simple ways (locally and deterministically in digital time steps).
Submitted by BhumikaPatel on Wed, 2006-01-25 14:15
The subject of protein folding
came up in one of my classes and although I had studied protein folding before, this time I began to wonder if protein folding is also an emergent system. Basically, protein folding is how a particular amino acid sequence folds itself into a conformation that is lowest in energy. The process it goes through can be described to be like a funnel, where the sequence tries to fold itself in different conformations while eliminating high energy conformations until it gets to the native state (the conformation lowest in energy). The idea that amino acids are simple units that when arranged in a particular sequence, always fold in a similar manner led me to believe that protein folding could be an emergent system. There is no architect or conductor in protein folding as the native state of the protein depends primarily upon how the particular amino acids in the protein associate with themselves.
Submitted by SarahMalayaSniezek on Tue, 2006-01-24 19:35
While reading “From the Head to the Heart”
, I was reminded of a discussion in my Behavioral Neuroscience class about getting the right answer. I think it is important here to state that it is not important to find an answer, but to “get it less wrong”. I absolutely love this phrase we used in Professor Grobstein’s class. Instead of looking at getting the right answer about Emergence and whatever else we are thinking about, we should be trying to figure out what it is not. We have all discussed what we think Emergence is and how it relates to the world.
Submitted by LindsayGold on Tue, 2006-01-24 19:14
...to anything we were discussing in class, but I'm a gamer. I'm sure I'm not the only one, either. But someone (possibly Flora?) mentioned a man named Will Wright
, the creator of The Sims
, and all their related expansions and franchise stuff. Great games, absolutely classic. They're largely in the "sandbox" style - you can't really win, you just keep going, dealing with events and continuing to manage your city or household or whatever. He's a highly acclaimed game designer, and also seen as something of a visionary in the gaming community. He has a new project in the works, under the title of Spore
Submitted by PaulGrobstein on Tue, 2006-01-24 17:58
Also interesting/not anticipated quite was the importance of recognizing that much of human behavior is, like that of other animals and of computer models, not the result of "thinking" or "intending". Yes, I triggered our collective rhythmic clapping but had no idea what the frequncy would be; that "emerged" as the result of a distributed organization with no conductor. I mentioned as another example Traffic Jams
, which in addition will give you another taste of NetLogo.
This raises an interesting question about "thinking" itself. Clearly "surprising" things can be created without "thinking". So what is "thinking" for? To prevent "surprise"? Or, perhaps, to create additional "surprising" things, things that would not otherwise have come into existence without thinking, perhaps even "surprising" to the thinker?
Submitted by DougBlank on Tue, 2006-01-24 00:40
On Wednesday, we will change directions a bit and head directly to computer modeling. There are two readings posted on the schedule
for Wednesday: first, take a look at the first two chapters of Stephen Wolfram's "New Kind of Science." Second, look over the pages on "Python 1D CA". The "Python 1D CA" will probably be not enough detail for some of you, and too much detail for another some of you. Keep in mind that we have a very diverse group.
I hope that everyone in the class will have their accounts soon, and you can try out the experiments. If you are following along our blog, all of the software that we will use in this course is freely available, so you can download it and follow along. And everyone is welcome to comment here.
Submitted by PaulGrobstein on Mon, 2006-01-23 17:25
Thanks, all, for rich conversation ... and apologies for not getting the timing quite right, building toward some things without leaving time to wrap them fully. It was in fact part and parcel of the rich conversation, with several issues becoming clearer in my mind as we talked through them. Here, in any case, is the bottom line, as it emerged ....
The diversity of things that come together in/around the topic of emergence might in principle be related in three somewhat different ways
- a random assembly of mysterious things that one might hope will be illuminated by emergence
- a set of different mysterious things that have some apparent similarities and hence might follow similar rules that operate in different circumstances (eg being "distributed organization")
Submitted by PeterOMalley on Mon, 2006-01-23 01:25
I've heard the term "emergence" applied to astronomy, and since I seem to be the only person studying astronomy in the class (though if I'm not, please say so!), I feel like I should say something about it. I admittedly don't know to much about it, but my understanding is that the concept of emergence is applied to the origin of large-scale structure in the universe; that is, galaxies, clusters of galaxies, and superclusters, the biggest structures after the universe itself. A Haverford alum, Ravi Sheth
, came to give a talk about this last semester, but I don't believe he used the term "emergence." He works with computer models of galaxies and such, and linked it to, among other things, the stock market and traffic.
Submitted by DougBlank on Sun, 2006-01-22 10:05
In class this week, we will be discussing Paul's "From the head to the heart
". Although I usually read everything on-line, you might prefer to have a hardcopy of this. In printing the paper out, I created a few versions that you may find useful, even for on-line reading or for printing---some have a larger font than others. Read more for the choices...
Submitted by JoshCarp on Wed, 2006-01-18 20:10
I've been interested by computer modelling approaches to evolution for some time now, and I've come across a few papers on the subject that might offer something to a discussion of emergence.
A sizeable part of evolutionary theory cannot practically be submitted to direct test. Evolution can only be observed in rare cases--among bacteria
in petri dishes or finches
on the Galapagos islands.
This is where computer modelling comes in. It has been applied extensively
to ideas about the evolution of cooperation
in social species. Studies of this sort typically examine simulated interactions among members of a population, pitting them against each other in games like the prisoner's dilemma
. Members of the population follow different strategies with different levels of cooperation. After some predetermined number of rounds of the game are played, a new "generation" is born, with its proportions of cooperators and defectors determined by the relative success of each strategy during the previous generation. This process is iterated over hundreds or thousands of generations. The entire simulation can be run with parameters--say, the payoffs and punishments of the game, or the initial proportions of each strategy--altered. Some configurations give rise to fixation of one strategy, others to a stable polymorphism, others to steady oscillations in strategy frequency, etc.