Scott Christley wrote:
This is often call the state explosion problem, and it becomes a
problem when state change is more than changing the value of a
variable but implies functional change as well. If you design a
model where you explicitly handle all of those states, that means
you need to explicitly write code for the function of the agent
for each states. What if the number of states is exponential?
I think that's overstating it a bit. A larger space means more
things are possible, but the interpreter of that space can still be
simple. A codon is simple and stable in spite of the fact a
larger genomes can code for more complex things. Similarly, the
instruction set of a CPU is small and finite and relatively
straightforward to get working compared to the virtually infinite
number of programs than can be written with that set of opcodes.
This might be no big deal, but another complexity is that under
different circumstances, the splicing process produces different
RNA. So the basic idea that a single gene (DNA) produces a single
Protein is not true, there are multiple proteins produced through
alternative splices.
Ok,1) the notion of alternatives and 2) information about how to
regulate the alternatives
In biology, a protein's function is defined by its structure but
that structure is not fixed, enzymes and other molecules often
change that structure, so a protein is considered to have
different conformations.
and 3) context dependency
Now you are faced with a scenario that the hyperspace is so large
that you cannot code in all of the possible interactions ahead of
time.
But it's mainly about computer runtime not human time (e.g. too
many coding details).