Self-study
The mathematics of the scientific theory known as "complexity" describes those phenomena that are not quite stable and not quite chaotic. ███ ████████ ███ ███████████ ██ ██████████ ███ ██ ████ ██ ████████ ████ ██████ ████████ ████ █████ █████████ ██████ █████ ██████ ███ ████████ ██ █ ████ ██████ ██ ████ ███ █████ █ ██████████ ███████ ██████████ ████ █████████ ████ █████ ██ ████ ████████ ████ ██████████ ██ ████████ █████ ████████ ████████████████ ████████████ ██████ ██ ██████████ █████████ ██ ██████████ ████ █████ ████ ███ ████████████ ████████████ ██████ ██████ ████ ████ ███ ██████████ █████████ ████████ ███████
Summary
Computer simulations based on the theory of complexity give the same results as what scientists have observed in the real world. Therefore, complexity is likely correct.
Notable Assumptions
The argument concludes that complexity must be correct based only on the fact that computer simulations of complexity match up to real world observations. In making that jump, it has to assume that, if computer simulations based on complexity give the same results as the real world, that helps demonstrate that complexity is correct. We’re therefore looking for a principle that explains that leap - that tells us explicitly that a computer simulation giving the same result as the real world means the theory the computer simulation is based on is likely correct.
14.
Which one of the following ███████████ ██ ██████ ████ █████████ ███ ███████████ ███████████
a
If computerized models █████ ██ █ ██████ ██████ ████ █████ ██████████ ████████████ ███████ ████ ████ ██████ ██ ████████ ████████
This fills the gap in the argument, and explains why the premise leads to the conclusion - the computer models based on complexity behave the same way as their real-world counterparts, therefore complexity is likely correct.
b
If a scientific ██████ ██ ████████ ████ ████████████ ████████████ ██████ █████ ██ ████ ██████ ██████ ████ █████ ██████████ █████████████
This goes in the wrong direction. We need to get from the claim that the models behave like the real world to the claim that the theory is correct - this assumption would move the other way.
c
If actual phenomena ███ ██ ████████ ██ ████████████ ███████ █████████ ██████████ ████ ██████████ ████████ ███ ███████████ ██ ███ ███████ ██████ ██████████ █████ ██████████
Leads to the wrong conclusion. This argument isn’t about what theories computers will eventually discover - it’s about whether a specific theory is correct.
d
If they evolve ███████ ████ ██████████ ██████████ ████████ ██████ ███ ███████ ██████ ██████ ███ ██████ ████████ █████ ██ ████ ██████████ █████████
Wrong trigger. Complexity isn’t trying to predict anything about computer models, it’s making a statement about what happens in the real world.
e
If computers verify ████ █████ ███ ████████████ ██████ ██ ███ ████████████ ██ ███████████ ████ ███ ████████ ██ █████ ██████████ ███ ████████ ██████████
Wrong trigger. The computer simulation in this case did not verify that there were any mathematical errors.