For today you should:
1) Check the performance of your Graph.py
2) Read Chapter 4 and answer the reading questions below.
3) Read the paper by Barabasi and Albert.
1) Chapter 4 reading questions
2) Explanatory models.
3) Thomas Kuhn.
For next time you should:
1) Read about Thomas Kuhn and "Objectivity, Value Judgement and Theory Choice."
2) Read Chapter 5 and prepare the reading questions below.
2) Continue to work on exercises at your pace.
WS: Social networks have high clustering because most links are local, but the presence of even a small number of non-local links reduces the average path length to a small near-constant.
BA: Social networks have high variability in degree; that is, most people have a small number of contacts, but a few people have a very large number. These people act as "hubs" that connect distant nodes and keep path lengths short.
Which is true?
Realism: Theories are either true or false depending on whether they correspond to reality.
But if "true" means perfect correspondence with reality, then all theories are trivially false.
In that case, what are the criteria for preferring one theory over another?
Structure of Scientific Revolutions:
1) normal science/paradigm shift
2) incommensurate paradigms
From Through the Looking Glass:
3) rejection of idealized models of scientific method
Reactions to SSR, from mild to strong
a) scientists are human, but the scientific method is still the goal of good science
b) theory choice is frequently under-determined by facts, other criteria also matter, but choices can be justified
c) science is no more objective than any other field of inquiry, theory choice is a personal preference, scientific consensus is mob rule
d) so-called "truth" is all relative, there are no "facts", science has no special claim on truth, it is just a tool the Man uses to keep the people down...
"Objectivity, Value Judgment and Theory Choice" is Kuhn's reaction to (d), where he makes an argument for something like #(b).
As a warmup, you might want to read:
Reading questions for "Objectivity, Value Judgment and Theory Choice":
1) What are Kuhn's criteria for theory choice?
2) What limitations does Kuhn acknowledge for using these criteria?
3) What is Kuhn's answer to the charge that scientific consensus is "mob psychology"?
Chapter 5 reading questions
1) In the context of a cellular automaton, what is a neighborhood? What kind of graph does this remind you of?
2) Why do we draw 1-D CAs with 2-D diagrams?
3) What's the difference between a list of lists and a Numpy array?
4) What is the connection between CADrawer and the Template Pattern?
5) What is the difference between a top-quality PRNG and a truly random process?
6) What is the principle of determinism, and what scientific discoveries cast doubt on it?
7) Are CAs physical models?
Next time we will come back to these questions:
1) What is universality?
2) What is the Principle of Computational Equivalence?
3) What is falsifiability? Why is it a good thing for a scientific theory to be falsifiable?