| reading |
[Dec. 10th, 2002|08:20 pm] |
Stephen Wolfram. A new kind of science.
reeding notes:
p.19. At first I did not believe that they could possibly be correct. ...then I realized that I had seen a sign of a quite remarkable and unexpected phenomenon: that even from very simple programs behavior of great complexity could emerge.
p.23. the key idea...was to ask what happens if one instead just looks at simple arbitrarily chosen programs, created without any spcific task inmind. How do such programs typically behave?
All one need to do is just set up a seq. of possible simple programs, and then run them and see how they behave.
p.24. on cellular automata: but modifying the rule just slightly one can immediately get a different pattern.
p.42. In the history of science it is fairly common that new technologies are ultimately what make new areas of basic science develop. (e.g. telesc. - astr., microscope - biology) ?any proof?
note: looks like this "new science" is the result of brain+computer symbiosis.
p.47. Thus there are two quite different reasons why it would have been difficult ..to discover before 1980. first, computers did not provide sufficient ease to conduct experiments; second: the new kinds of intuition could not have been developed without extensive exposure to practical computing.
note: he essentially experiments on computers and computing patterns
p.105. ch 3 concl. ...to get complexity in the overall behaviour of a system one needs to go beyond some threshold in the complexity of its undelying rules. ...the threshold is typically extremely low. Once the thresh. for complex behaviour has been reached, ...adding complexity to the underlying rules doesn 't lead to any perceptible increase at all in the overall complexity of the behaviour. ..But what we have seen ..is that at an overall level the typical types of behaviour that occur are quite universal, and a re almost completely independent of the details of underlying rules. p. 108. even if we do not know all the details of what is inside some specific system in nature, we can still potentially make fundamental statements about its overll behaivor.
p. 109. computer enables precise experiments - combine the best of both theoritcal and exper. approaches to science.
p. 110. The consequences of this fact for computer experiments ...imply that theres nver an immediate reason to go beyond studying systems with rather simple underlying rules. ..in my experience the single most common mistake in doing computer experiments is to look at systems that are vastly more complicated than is necessary. Note: !!very good for the 4 parts rule!!!
to be continued.... |
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