Sciences of the Artificial, part two

Herb Simon joke on decomposable systems/chunking.

Today's class discussion questions
Simon, ch. 7, 8

Core Questions

In Chapter 8 of the Sciences of the Artificial, Simon says "Roughly, by a complex system I mean one made up of a large number of parts that interact in a nonsimple way. In such systems, the whole is more than the sum of the parts, not in an ultimate, metaphysical sense, but in the important pragmatic sense that, given the properties of the parts and the laws of their interaction, it is not a trivial matter to infer the properties of the whole. In the face of complexity, an in-principle reductionist may be at the same time a pragmatic holist." -- How should we reconcile this perspective (first expressed in the 1981 edition of this book) with the one expressed 5-6 years later in the debate between Simon and Greeno?

In Simon's way of looking at emergent behavior, a component's short-term behavior can be described independently from other components; interactions are slower to manifest and only really matter in the longer-term. Is this way of thinking about emergence useful? Valid? Does it allows us to capture key aspects of emergent behavior, or are things irreducible?

Simon also says, "By adopting this weak interpretation of emergence, we can adhere (and I will adhere) to reductionism in principle even though it is not easy (often not even computationally feasible) to infer rigorously the properties of the whole from knowledge of the properties of the parts. In this pragmatic way, we can build nearly independent theories for each successive level of complexity, but at the same time, build bridging theories that show how each higher level can be accounted for in terms of the elements and relations of the next level below." -- does this way of addressing systems address the kind of concerns that Greeno, for instance, brought up? Does it enable us to understand educational systems as wholes?

Secondary Questions

Can the interactions between students in a school be understood as a nearly decomposable system?

How would be represent learning as a nearly decomposable, hierarchic system? What are some positives to taking this tack?

Simon does not believe that many systems are characterized by sudden shifts from stable behavior to catastrophe (or at least that theory along these lines isn't particularly generative). Economic systems clearly can be prone to sudden shifts, and Nassim Talib argues that our inability to predict and react quickly enough to this is due to a fundamental assumption of normality in our statistical models. Are there ways in which education/learning/learners may sometimes look like a stable system which suddenly goes off the rails? What about online learning systems?