feat: add algorithmic countability

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Kristofers Solo 2025-06-13 19:48:44 +03:00
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commit 2c0b0785a2
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@ -13,6 +13,7 @@
#let rej = $q_"rej"$
#let acc = $q_"acc"$
#let halt = $H A L T I N G$
#let halt2 = $halt 2$
= Tjūringa Mašīnas
@ -36,7 +37,7 @@ Nosimulēt stāvēšanu uz vietas jeb $d=0$ var sādi:
+ Izdomāt, kā aizstājot simbolus ar $*$ var pārbaudīt virknes derību.
+ Atcerēties par secību -- aiz $a$ var sekot tikai $b slash c$, aiz $b$ var sekot tikai $c$, utt.
+ Doties katrā no virzieniem var doties arī līdz galam jeb tukšumam $\_$.
+ Vairāklenšu $TM$ pārraksta pirmo daļu līdz $\#$ uz otras lentes un salīdzina.
+ Vairāklenšu #TM pārraksta pirmo daļu līdz $\#$ uz otras lentes un salīdzina.
== Piemērs
Vai ieejas virknē $a^n b^n c^n$, kur $n>0$
@ -237,13 +238,13 @@ Given a problem $halt 2(M, x, y) = 1$ where turing machine $M$ halts on at least
one of the inputs $x$ or $y$, prove and show that it can or can't be reduced to
$halt(halt <= halt 2)$.
To prove that the problem $halt 2(M, x, y)$ can be reduced to $halt$, we need to
show that we can construct a Turing machine that solves $halt 2$ using a
subroutine for solving $halt$.
To prove that the problem $halt2(M, x, y)$ can be reduced to #halt, we need to
show that we can construct a Turing machine that solves #halt2 using a
subroutine for solving #halt.
Let's assume we have a Turing machine $H$ that solves the $halt$ problem.
We will construct a new Turing machine $H 2$ that solves the $halt 2$ problem
using H as a subroutine.
Let's assume we have a Turing machine $H$ that solves the #halt problem.
We will construct a new Turing machine $H 2$ that solves the #halt2 problem
using $H$ as a subroutine.
The Turing machine $H 2$ works as follows:
+ Given inputs $M$, $x$, and $y$.
@ -264,17 +265,17 @@ Now, let's analyze the reduction:
one of the inputs $x$ or $y$.
In this case, $H 2$ will also halt and accept, because it successfully
simulates $H$ on both inputs and accepts if $H$ accepts either of them.
Thus, $halt 2$ is reduced to $halt$.
Thus, #halt2 is reduced to #halt.
- If $halt2(M, x, y) = 0$, it means that Turing machine $M$ does not halt on
both inputs $x$ and $y$.
In this case, $H 2$ will also not halt and will reject, because it simulates
$H$ on both inputs and rejects if $H$ rejects both of them.
Thus, $halt 2$ is reduced to $halt$.
Thus, #halt2 is reduced to #halt.
Therefore, we have shown that the problem $halt 2$ can be reduced to $halt$ by
Therefore, we have shown that the problem #halt2 can be reduced to #halt by
constructing a Turing machine $H 2$ that uses $H$ as a subroutine.
This reduction demonstrates that $halt 2$ is computationally no harder than
$halt$, implying that $halt 2$ is at least as undecidable as $halt$.
This reduction demonstrates that #halt2 is computationally no harder than
#halt, implying that #halt2 is at least as undecidable as #halt.
= Daļēja atrisināmība
== Info
@ -307,6 +308,40 @@ $A$ -- daļēji atrisināma, ja ir Tjūringa mašīna $T$:
#teo[$A$ -- daļēji atrisināma tad un tikai tad, ja $A$ -- algoritmiski sanumurējama.]
= Algoritmiskā sanumurējamība
= TM darbības laiks
== Info
- Kopa $A$ ir sanumurējama, ja $A={x_1, x_2, ...}$
- Kopa $A$ ir algoritmiski sanumurējama, ja ir Tjūringa mašīna, kas izdod virkni
$x_1, x_2, ...$, kurai $A={x_1, x_2, ...}$
#let DL = $D L$
#let IL = $I L$
Divu lenšu #TM, kur viena ir klasiska darba lente (#DL) un otra ir izvada
lente (#IL) (tikai rakstīšanai).
== Piemērs
Pamatot, ka kopa ${a^k b^k mid(|) k>=0}$ ir algoritmiski sanumurējama.
+ Uzraksta uz izejas lentes tukšu vārdu.
+ Uzraksta vienu $a$ uz darba lentes.
+ Atkārto:
+ Uz ieejas lentes uzrakstām tikpat $a$, cik bija uz #DL;
+ Uz izejas lentes uzrakstām tikpat $b$, cik $a$ bija uz #DL;
+ Uz izejas lentes uzrakstām $\_$;
+ Uz darba lentes pierakstām klāt vienu $a$.
+ Izejas lente $=epsilon, a b, a a b b, a a a b b b,...$
== Piemērs
Pamatot, ka kopa ${x \# x mid(|) x in {a, b}^* }$ ir algoritmiski sanumurējama.
+ Uz darba lentes iet cauri visiem $x$.
+ Katram $x$ uz izejas lentes uzraksta $x \# x$.
+ Uz izejas lentes uzraksta $\#\_$.
+ Uz darba lentes uzraksta $a$.
+ Atkārto:
+ Pārraksta darba lentes saturu $x$ uz izejas lenti;
+ Uzraksta $\#$ uz #IL, vēlreiz pārraksta $x$ uz #IL, uzrakstām $\_$ uz #IL.
+ Uz #DL nomaina $x$ pret nākošo vārdu.
= #TM darbības laiks
= NP (neatrisināmas problēmas)
= Sarežģītības klases