Emergence Biology 361 = Computer Science 361 Bryn Mawr College Spring 2006

Some Blog Thoughts When I think of emergence, I feel like I have to "change my glasses" (not that I wear them) and put on something that makes the world fresh again. Something that gives me back that sense of wonder that we all had when we were children. ... Julia_Ferraioli Just posting to say that I have no clue what to do a project about. (Neither does jferraio, she says, though I have great faith that she'll come up with something awesome.) I hope I'm not alone. Coding, fine, I can do that. But I just don't know where to start... LindsayGold When I try to explain the emergence course to my friends I start with the idea that simple rules lead to great solutions ... Stephanie Hilton Life and emergence "The line between living organisms and machines has just become a whole lot blurrier ..." I heard this headline on the way in to school yesterday morning and dug up this link to it. Sounds pretty exciting ... Also, I thought one of the pictures was interesting.. have a look at the snail neurons.. is that why netlogo calls them turtles? ... Leslie I was really excited because I thought maybe something else entirely had been accomplished--like a chip in your brain that actually participates in information processing cooperatively with neurons ... Jesse A Depression Switch I saw this article on Slashdot today touting the "first digital simulation of an entire life form," ... What I found particularly interesting was the discussion that ensued on Slashdot: many of the posters touched on themes that have come up repeatedly in class. Several tackled the more philosophical "What is life?" question and asked whether or not a life form that exists solely in a virtual context can be "alive." Some argued for and others against, but a sizable contingent argued for the idea that "life is not a binary distinction"--that is, there is a continuum of "life" along which some things are more alive than others. I thought that this concept dovetailed quite nicely with some of our earlier class discussions ... Jesse I am not convinced at all that there is a significant amount of emergent activity in Spore. There is a lot of talk in the gaming press about the "evolution" in Spore and so on, but it is not really evolution at all! If you watch the video, it shows that as time passes you gain "evolution points" which allow you to change your creature by adding limbs or increasing its speed. That does not sound like evolution to me. It sounds more like intelligent design, which is essentially the opposite of emergence ... DavidRosen (see also Julia and Josh) Rationality, the Brain and Emergence During Monday's lecture Professor Blank told us about a split into two separate approaches to studying artificial intelligence. The split is between the rational models and emergent models. Professor Blank writes that "These two paradigms, in my opinion, have little to do with one another. That is, emergent models can certainly show rational, rule-like behavior. But the implementation of emergent models have nothing to do with how rational models operate." ... I don't understand how this dichotomy is possible! I agree that emergent models can show logical "rational" behavior ... However, I feel like rational models could have a role in the implementation of emergent models. The only reason I can seem to find to support this intuition is the way in which I imagine the human brain works. It seems to me that the brain is a rational model of neurons which calculate and makes decisions, while the way in which we experience consciousness is an emergent phenomena resulting from the rational model of these neurons ... LauraKasakoff I think Professor Blank was using the word "rational" in the sense of "logical". That is, the "rational" approach to AI usually focuses on explicit operations and symbols, and recursively applying these operations until the goal is reached ... An emergent approach would use more bottom-up systems like genetic algorithms and neural networks to solve this problem. Other ways to think of rational vs. emergent might be symbolic vs. subsymbolic, algorithmic vs. learning, top-down vs. bottom-up, and so on ... DavidRosen You make a good point when you point out that (and here I paraphrase) I need a rational system to write the computer program in order to implement my emergent neural network. But the level of the computer doesn't have much to do with the level of the neural network. Likewise, the level of the neural network doesn't have anything to do with logic, or even "making decisions". All the network level is doing is adding, multiplying, and number squashing ... What the two systems do have in common is their behavior. Both can compute the same "functions". Maybe one does it through a lookup table, the other by adding, multiplying, and squashing. The network goes through a level of nodes and numbers. This is the level that does the actual "thinking". In the lookup table, there is no other level. ... This is a critical difference, I think. You could say that neurons are being rational and deciding to make decisions. But the level that they are acting is at a different level than what they are actually computing ... Another way to say this is that I think Einstein would make a really lousy neuron. Why? Because he would be thinking about whether he should fire or not based on trying to make sense of the signals around him. But the "sense" isn't made at this level, but at level above this one---the network that Albert would be embedded in. It emerges from the network of the micro-Eisteins' interactions ... So, a system that computes "emergently" (or, as David says, "subsymbolically") computes below the level of the meaning. On the other hand, rational systems compute at the level of the meaning ... We should continue this discussion ... DougBlank

What are the relations among living organisms, machines, emergence, intelligent design, rational, logical, meaning, goals (purposes)? See what light brains and biological evolution shed on that question ...

Brains and machines

The brain as a material entity interacting entities (agents) with fairly simple physically characterizable properties and interaction rules - neural networks = interconnected agents working in an environment capable in principle of all logical operations machine? computer? a Turing device? that also has autonomy and randomness modifiability, output/input coupling (and hence purposive behavior, without "purpose"?) specific architecture no purposive designer machine? capable of things beyond capabilities of computer? Turing machine? creativity free will? transcending limitations of logic (choosing completeness over consistency)

Modifiability: a useful distinction between two kinds of learning

• supervised
  • does "generalize"
  • doesn't necessarily (usually?) learn what supervisor has in mind
  • varies with (among other things) random starting position
• unsupervised
  • Kohonen networks (alternate)
  • Hopfield Networks (alternate)
  • can be used for various purposes (more or less successfully depending on network and purpose)
  • at least as interesting for what it does without designer purpose
• ie with and without an external reference model by which to evaluate performance (no conductor, no designer?, like brain?)

Bipartite architecture: a useful (?) distinction between .... meaning/no meaning?

• The conscious/unconscious distinction
  • More examples
• Adaptive behavior, learning ("rationality"?) in the unconscious
• Distinctive properties of consciousness
  • beyond hillclimbing (to evolve?)
  • capability to both use and escape from the limitations of logic (become one's own designer)
    • make "meaning" (and "purpose", and conductors/designers) a significant causal factor in the universe
    • free will

Brain is a machine (ie material) but is unlike any machine so far built by humans

• not built for a "purpose"; evolved under conditions that encouraged expression of multiple capabilities, including the ability to generate new, surprising things
• has features that make it non-optimal for particular "purposes"
• the same features give it the capability to transcend capabilities of general purpose logical machines
• while smaller units process in ways that lack "meaning", the bipartite architecture of the brain provides a way to distinguish processing that lacks meaning from processing that has meaning, ie one part of the brain can serve as observer/meaning giver for the entire brain (as well as for other things)
• the brain creates and is the exemplar of both "conductors" and "architects"
• "purpose" and "meaning" are emergent, your brain has the wherewithal to create them, need not have them to do so
• So .... where did the brain come from? Evolution ...

Biological evolution from Darwin to the present (alternate):
evolution too can be directed (evolutionary algorithms, programming, see also Biomorph Breeder) but exists too in importantly undirected form ... biological evolution from Darwin to present

• diversity but no essential characteristics
• no architect, conductor
• no normative hierarchy, time/history dependent (contrast Haeckel)
• no pre-existing "objective"
• agents are both products of and creators of ongoing change dependent on randomness
• ongoing exploration of what might be

Brain evolution

"We are all active and interacting entities in a long-standing exploration of possible forms of material organization which has been enriched by story-telling and agency" ... that are themselves characteristics of brains we all possess.

Re course projects:
Don't worry so much about being "logical"/"rational" or finding "solutions". "... intelligent design ... is esentially the opposite of emergence". "Make the world fresh again". "Simple rules lead to ..." "something awesome". Play ... and THEN make "meaning".

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