Personīgi man šķiet, ka ārpus tīrās matemātikas (ar uzsvaru uz "tīrās", jo bezgalību empīriska eksistence joprojām ir ļoti atklāts jautājums) "domas par bezgalīgo" ir galvenokārt konceptuāla rotaļāšanās.

(Reply to this) (Thread)

Kāds ir "konceptuālas rotaļāšanās" evolucionāri bioloģiskais skaidrojums?

(Reply to this) (Parent) (Thread)

Zinātkāre un iztēle (the latter being just a folksy word for conceptual and counterfactual modelling) kā adaptīvs pielāgojums. Attīstoties kognitīvajam aparātam, tas pats basic mehānisms, kas sākotnēji tika izmantots tādām lietām, kā teritorijas apzināšanai un briesmu laicīgai novērtēšanai, ir ieņēmis jaunus domēnus.

Complex machinery develops its own agendas. Brains – cheat. Feedback loops evolve to promote stable heartbeats and then stumble upon the temptation of rhythm and music. The rush evoked by fractal imagery, the algorithms used for habitat selection, metastasize into art. Thrills that once had to be earned in increments of fitness can now be had from pointless introspection. Aesthetics rise unbidden from a trillion dopamine receptors, and the system moves beyond modeling the organism. It begins to model the very process of modeling. It consumes ever-more computational resources, bogs itself down with endless recursion and irrelevant simulations. Like the parasitic DNA that accretes in every natural genome, it persists and proliferates and produces nothing but itself. Metaprocesses bloom like cancer, and awaken, and call themselves I.

(Reply to this) (Parent) (Thread)

Jā, protams, Bahs, impresionisms un kabuki teātris - viss kaut kas līdzīgs vēzim, pointless un traucējošs "evolucionārajiem procesiem". Kurš normāls, vesels cilvēks buys ths shit.

(Reply to this) (Parent) (Thread)

Mēģini tik ļoti nepārdzīvot.

(Reply to this) (Parent)

Vārdu sakot, a classical case of explaining away [things that are too complex and nuanced so just lets call them "irrelevant simulations" that produce "nothing but itself").

Pat ja pieņem šo vague spēli - nu labi, brains cheat. Nu un, kā šī cītošana "pointless introspection" ir skaidrojama evolucionāri bioloģiski? Why so much waste and pointlessness?

(Reply to this) (Parent) (Thread)

Because evolution doesn't optimise for efficiency and doesn't do garbage collection. Because evolution works as adaptation-execution, not utility-maximisation.

Gar evolucionāro procesu malām uzkrājas t.s. spandrel characteristics, kas ir vai nu no sākotnējo domēnu (vides u.c. pārmaiņu dēļ) zaudējuši pielāgojumi, vai arī pielāgojumu blakusprodukti, kas paši nepilda izdevīgas funkcijas, bet, tajā pašā laikā, arī netraucē organismam nodot tālāk savu alēļu komplektu un, attiecīgi, saglabājas un piedzīvo savu, paralēlu, izmaiņu secību līdzi uz nākamajām paaudzēm. Nav izslēgts, ka gadījumā, ja šīs "fīčas" būtu vēl enerģētiski neizdevīgākas, tās arī būtu tikušas aizselektētas projām.

(Reply to this) (Parent) (Thread)

Evolūciju reizēm sauc par optimizācijas algoritmu. Es zinu, no kurienes nāk tie termini, bet tavs otrais teikums attiecas uz individuālajiem organismiem, nevis uz evolūciju vispār.

Pārējais ir vienkārši spekulācija, just so story "es neredzu jēgu, tātad tās nav", explaining away.

(Reply to this) (Parent) (Thread)

Evolūcija kā tāda ir optimizācijas algoritms šauri tehniskā nozīmē, tikai tur ir jāņem vērā tas, ko tā optimizē. Par pārējo – well, es esmu atvērts arī citām hipotēzēm.

(Reply to this) (Parent)

Kas attiecas uz "čītošanu", tad tas ir izplatīts ģenētisko algoritmu un citu constraint-satisfaction procesu darbības aspekts, ko izraisa šo procesu un to darba vides īpašību mijiedarbība. Relevants ekscerpts no N. Bostroma "Superintelligence":

Even simple evolutionary search processes sometimes produce highly unexpected results, solutions that satisfy a formal user-defined criterion in a very different way than the user expected or intended.

The field of evolvable hardware offers many illustrations of this phenomenon. In this field, an evolutionary algorithm searches the space of hardware designs, testing the fitness of each design by instantiating it physically on a rapidly reconfigurable array or motherboard. The evolved designs often show remarkable economy. For instance, one search discovered a frequency discrimination circuit that functioned without a clock—a component normally considered necessary for this function. The researchers estimated that the evolved circuit was between one and two orders of magnitude smaller than what a human engineer would have required for the task. The circuit exploited the physical properties of its components in unorthodox ways; some active, necessary components were not even connected to the input or output pins! These components instead participated via what would normally be considered nuisance side effects, such as electromagnetic coupling or power-supply loading.

Another search process, tasked with creating an oscillator, was deprived of a seemingly even more indispensible component, the capacitor. When the algorithm presented its successful solution, the researchers examined it and at first concluded that it “should not work.” Upon more careful examination, they discovered that the algorithm had, MacGyver-like, reconfigured its sensor-less motherboard into a makeshift radio receiver, using the printed circuit board tracks as an aerial to pick up signals generated by personal computers that happened to be situated nearby in the laboratory. The circuit amplified this signal to produce the desired oscillating output.

In other experiments, evolutionary algorithms designed circuits that sensed whether the motherboard was being monitored with an oscilloscope or whether a soldering iron was connected to the lab’s common power supply. These examples illustrate how an open-ended search process can repurpose the materials accessible to it in order to devise completely unexpected sensory capabilities, by means that conventional human design-thinking is poorly equipped to exploit or even account for in retrospect.

The tendency for evolutionary search to “cheat” or find counterintuitive ways of achieving a given end is on display in nature too, though it is perhaps less obvious to us there because of our already being somewhat familiar with the look and feel of biology, and thus being prone to regarding the actual outcomes of natural evolutionary processes as normal—even if we would not have expected them ex ante. But it is possible to set up experiments in artificial selection where one can see the evolutionary process in action outside its familiar context. In such experiments, researchers can create conditions that rarely obtain in nature, and observe the results.

(izcēlums mans)

(Reply to this) (Parent)