# NP Completeness

• Decision problem (yes/no)
• Search problem (find the answer)
• Optimization problem

## Nondeterministic Turing machine

• A Deterministic Turing Machine executes one instruction at each point in time. And then depending on the instruction, it goes to the next unique instruction.
• A Nondeterminism is now typically represented by giving a machine an extra input, the certificate or witness.

## NP

• NP: Nondeterministic polynomial-time
• NP Problem: 在 polynomial-time 时间内可以验证的问题。
• $$NP \overset{?}{=} P$$: 是否所有能在 polynomial-time 时间内验证的算法都能在 polynomial-time 内被解决

## Reduction and NP-Complete Problems

An NP-complete problem has the property that any problem in NP can be polynomially reduced to it.

### reduction 约化

To prove a reduction $$A\le_P B$$ , we require 3 steps

1. We have to find the mapping function $$f$$ and show that it runs in polynomial time.
2. for all $$x \in A$$, then $$f(x) \in B$$
3. If $$f(x)\in B$$, then $$x\in A$$

• A polynomial-time algorithm for $$Q_2$$ would sufficiently imply a polynomial-time algorithm for $$Q_1$$.
• $$Q_1$$ can be polynomially reduced to $$Q_2$$

### 常见 NPC 问题

• SAT Problem(第一个被证明为 NPC 的问题): 给定一个n个布尔变量组成的布尔表达式，判断其有没有可能为真
• Hamiltonian cycle Problem: 给定一个图，判断是否有一个simple cycle恰好经过每个顶点一次
• Traveling Problem: 给定一个带权图，问是否存在一个simple cycle经历过每个节点且经历边的权重和不超过K?
• Vertex Cover Problem: 给定一个图，判断是否存在其一个大小不超过K的点集，使得图中任一条边至少有一个顶点在这个点集中
• clique problem: 给定一个图，判断图是否有一个大小至少为K的完全子图（团）。

## NP-Hard

If a NP-Hard problem is in NP, it is a HP-complete problem. ### 常见NP-hard问题

• 所有NP-Complete问题
• Halting problem(不属于NP-Complete)

## Formal-language Theory*

• An alphabet $$\Sigma$$ is a finite set of symbols
• A language $$L$$ over $$\Sigma$$ is any set of strings mode up of symbols from $$\Sigma$$
• Denote empty string be $$\varepsilon$$
• Denote empty language by $$\emptyset$$
• Language of all strings over $$\Sigma$$ is denoted by $$\Sigma^{\star}$$
• The complement of $$L$$ is denoted by $$\Sigma^{\star}-L$$
• The concatenation of two languages $$L_1$$ and $$L_2$$ is the language $$L=\{x_1x_2: x_1\in L_1\ {\rm and}\ x_2\in L_2\}$$
• The closure of Kleene star of a language $$L$$ is the language $$L^{\star}=\{\varepsilon\}\cup L\cup L^2\cup L^3\cup \cdots$$, where $$L^k$$ is the language obtained by cocncatenating $$L$$ to itself $$k$$ times