Notes for the Lifebox, the Seashell, and the Soul - Rudy Rucker

Notes for The Lifebox, the Seashell, and the Soul, by Rudy Rucker
the wall, or if (oh no!) there’s a sudden power outage. In this event you might end up with
half the old microcode and half the new microcode, and the two will no doubt be
incompatible and your machine won’t run at all. At this point, you’d call on the services of
an ueber-geek to reflash the BIOS from scratch.
The instructions that the chip reads out of the memory are called machine language.
Everything is a Program
Philosophical ontology and computer science's Object Oriented Programming (OO)
as in C++ or Java.
Everything is mathematics Everything is a set Everything is an object.
Objects are better than sets, as they have function pointers, they are a verb as well as
a noun.
An interesting thing about OO (object-oriented) languages is how they are like set
theory. We build up class definitions from the primitive byte variables (of various standard
lengths, recall that a floating point real is just four(?) bytes, for instance) like the way set
theorists build up all of mathematics from commas and pairs of brackets. Objects are even
better than sets, though, as they contain function pointers and corresponding blocks of code,
that’s a cool thing about the von Neumann architecture is that we have instruction pointer
and data pointer, so we crawls over both data and code.
Software engineering. Teaches us to look for patterns in our lives.
Activator-Inhibitor CA Rule
My rules have a definition of the following form, where I write a and b for activator
and inhibitor levels.
(Avoid division by 0) IF (b > bMin) THEN bSafe = b ELSE bSafe = bMin.
(Activator) aNew = a + aDiffuse • (aNabeAvg - a)
+ sDensity•a•a/(bSafe • (1 + aSaturation•a•a))
+ sDensity • aBase
- aDecay • a.
(Inhibitor) bNew = b + bDiffuse • (bNabeAvg - b)
+ sDensity•a•a
- bDecay • b.
(Clamp) Clamp both a and b to be in the range [0, abMax].
Kaneko-Abraham Rule
Their idea was to combine diffusion and the logistic maps as follows. Suppose I
write pop for a cell’s current population value, and newpop for the new value that I want to
compute. At each update each cell computes a diffusion term and a poplogistic term based
on a logistic parameter A and a diffusion parameter B. The parameters A and B are the same
for each cell.
diffusion = B•(Average of neighboring population values - pop)
poplogistic = Logistic(A, pop)
newpop = poplogistic + diffusion
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