if you happen to read about new technologies , you are most likely to hear words Artifical intelligence more often than any other words. AI itself is probably the most oustanding creation of human kind which is largely unxplored and growing exponentially if i can say.

如果您偶然阅读有关新技术的信息，那么您最有可能比其他任何单词更常听到“ 人工智能”一词。 人工智能本身可能是人类最杰出的创造，如果我能说的话，它在很大程度上是不受欢迎的，并且呈指数增长。

AI is about unlishing one of the most amazing thing in the universe , Intelligence. the technology that can learn much faster than us, solve computationaly hard problem human like me or you can’t solve with same speed and accuracy.

人工智能即将揭开宇宙中最神奇的事物之一- 智能 。 可以比我们学习更快的技术，可以解决像我这样的人类难以解决的计算问题，或者您无法以相同的速度和准确性来解决。

What is AI anyway ?

反正什么是AI？

if you think about AI, in a context of machine or technology you think about intelligent machine or intelligent softwares. lets focus on the word intelligence.

如果您考虑AI，则在机器或技术的上下文中，您会想到智能机器或智能软件。 让我们专注于智能这个词。

We often tend to use word intelligence to describe things we don’t know how to explain or how it literaly works, if we can explain them we just say they are algorithm or formulas designed for a specific task . It’s only intelligence if we can’t explain then. this definition implies that anything we design is not intelligent because we would know how it works.

我们经常倾向于使用词智能来描述我们不知道如何解释或它如何按字面意义工作的事物，如果我们可以解释它们，我们只是说它们是为特定任务设计的算法或公式。 如果我们不能解释的话，那只是情报。 这个定义意味着我们设计的任何东西都不是智能的，因为我们会知道它是如何工作的。

Like us human being we consider ourselves as intelligent because we don’t realy understand well how our brains works. Once we understand that we will not consider ourselves as intelligent anymore . or imagine yourself studying mathematics for the first time, you might wonder how your teacher can solve those simple mathematics problems , but when you grow up you realise that it was simple and you might not consider your primary math teacher as intelligent person if you are asked.

像我们人类一样，我们认为自己很聪明，因为我们无法真正理解大脑的运作方式。 一旦我们了解到我们将不再认为自己是聪明的。 或想象自己是第一次学习数学，您可能想知道您的老师如何解决这些简单的数学问题，但是长大后您会意识到这很简单，如果您被问到，您可能不认为您的主要数学老师是聪明的人。

but that’s not how we should define intelligence, for AI to be productive the concept of intelligence should be defined in a concept of task , for example if my goal is to plan flights with a lowest possible cost and my system is able to do it with a decent of success, i consider my system as intelligence at flight planning . it just turns out that human are intelligent in doing a lot of different things .Intelligent systems tends Apply concept and techniques like search, probabilistic planning and logic to achieve a certain goal.

但这不是我们应该定义情报的方式，为了使AI富有生产力，应该在任务概念中定义情报的概念，例如，如果我的目标是以尽可能低的成本计划飞行并且我的系统能够做到这一点为了取得成功，我认为我的系统是飞行计划中的智能。 事实证明，人类在做很多不同的事情上都是聪明的。智能系统趋向于应用诸如搜索，概率规划和逻辑之类的概念和技术来实现某个目标。

to design an intelligence system one must understand the task or problem domain.

设计智能系统必须了解任务或问题领域 。

We refer to a system or AI program as the Agent, and the surroundings or anything that can influence or have an impact on our system’s behaviour the environment. You may only consider the software as the agent and the other hardware components would be external to the agent and that’s part of the environment. or you might consider whole system as the agent, it realy depend on context.

我们将系统或AI程序称为“代理”，并将周围环境或任何可能影响或影响我们系统行为的环境称为环境。 您可能只将软件视为代理，而其他硬件组件将在代理外部，而这是环境的一部分。 或者您可以将整个系统视为代理，它实际上取决于上下文。

lets take an example of the agent and its environment. for example like a self driving car , we might consider a car as an agent and the surroundings as environment ,whether its something near our agent, agent position in the road, road width, distance from traffic light or may be our vehicle current speed. those are some properties that define our agent environment states.

让我们以代理及其环境为例。 例如，就像自动驾驶汽车一样，我们可能会认为汽车是一种媒介，而周围环境则是环境，无论它是否靠近我们的媒介，媒介在道路上的媒介位置，道路宽度，与交通信号灯的距离，或者可能是我们的车辆当前速度。 这些是定义我们代理环境状态的一些属性。

An agent interact with the environment by sensing its properties and its known as perception.

代理通过感测其特性及其被称为感知的方式与环境进行交互。

we need state of the environment on every stage to be able to examine our agent, define the next move towards our goal state.

我们在每个阶段都需要环境状态，以便能够检查我们的代理人，定义朝着目标状态迈出的下一步。

The process of which the agent decide what action to take based on perceived input is known as cognition.

代理根据感知到的输入决定采取何种行动的过程称为认知。

as you can guess much of discussion about AI focus on cognition (reasoning and decision making ) just human like behaviours. like on self driving car example the agent can perceive the traffic light state and decide whether to stop or keep going.

您可能会猜到很多关于AI的讨论都集中在人类(如行为)的认知(推理和决策)上。 就像在自动驾驶汽车上一样，座席可以感知到交通信号灯的状态并决定要停止还是继续行驶。

Some agent directly associate their action with what is perceived or have very simple pre programed behaviours like an automated light that sense something and turn on the light automatically these are referred to as reactive or behaviour based agents.

一些代理直接将其动作与所感知的行为或具有非常简单的预编程行为(例如，自动感应某些东西并自动打开灯的行为)相关联，这些被称为基于React或行为的代理。

On the other side some agent delibarate in the forms of non trivial processes such as game playing agent or flight planner . we can classify this agent depending on process they do like planning agents …, just keep in mind that it’s simple to accomplish complicated behaviour by layering simple reactive control.

在另一方面，一些代理人以非平凡的方式进行审议，如游戏代理人或飞行计划员。 我们可以根据他们像计划代理一样执行的过程来对该代理进行分类……，只需记住，通过分层简单的React性控制即可轻松完成复杂的行为。

人工智能的学习类型 (Types of Learning in Artificial Intelligence)

When someone asks you to describe different types of artificial intelligence systems, you might classify them based on their functionality or its evolvement .

当有人要求您描述不同类型的人工智能系统时，您可以根据其功能或它的发展对其进行分类。

Lets start from evolvement, there are three steps AI can deevelop or be evolved .

让我们从进化开始，AI可以发展或进化三个步骤。

• Artificial Narrow Intelligence人工智能
• Artificial General Intelligence人工智能
• Artificial super intelligence人工超级智能

Artificial Narrow Intelligence: is a stage of AI which involves machine that can only perform predefined tasks, simple machine has no thinking capability at this stage. most of the current AI systems far into this stage i guess.

人工智能 ： 人工智能的一个阶段，涉及只能执行预定义任务的机器，简单机器在此阶段没有思考能力。 我猜目前大多数AI系统都已经进入了这个阶段。

Artificial General Intelligence: At this stage machines have the ability to think and make decisions just like humans do, and we are not far off this stage currently.

人工智能：现阶段 机器具有像人类一样思考和做出决定的能力，我们目前离这个阶段并不遥远。

Artificial super intelligence: at this stage the machine have the ability to outperform humans. we are kind of far off this stage but people described it in some movies,where machine have taken over the world. and we are better off this i think.

人工智能：在此阶段，机器具有超越人类的能力。 我们离这个阶段还很遥远，但是人们在一些机器已经占领了世界的电影中对此进行了描述。 我认为我们会更好。

根据AI系统的功能 ，AI可以分为以下几种类型： (Based on the functionality of AI systems, AI can be classified into the following types:)

• Reactive machines AIReact机器AI
• Limited memory AI有限的内存AI
• Theory of Mind AI心灵理论
• Self-aware AI自我意识的AI

Reactive machines AI: The most basic types of AI systems have the ability neither to form memories nor to use past experiences to inform current decisions, its purely reactive . for example like a chess playing agent which observe oponent moves and its position to decide next best move.

React性机器AI：最基本的AI系统类型既不能形成记忆，也不能利用过去的经验来指导当前的决策，这是纯粹的React性。 例如象国际象棋棋子那样观察对手的动作及其位置来决定下一个最佳动作。

Limited memory AI : AI can make informed and better decisions by looking into the past data from its memory. for example self driving cars can look into past decisions and their effect to decide which action to take in a certain scenario.

有限的内存AI： AI可以通过查看内存中的过去数据来做出明智的决策。 例如，自动驾驶汽车可以查看过去的决策及其影响，以决定在特定情况下应采取的行动。

Theory of Mind AI: This kind of AI mainly focuses on emotional intelligence, this tipe of AI is not only the form representations about the world, but also about other agents or entities in the world.

心智理论AI：这种AI主要关注情绪智力，AI的这个秘诀不仅是关于世界的形式表示，而且也是关于世界上其他主体或实体的形式表示。

Self-aware AI: This kind of AI is a bit far in view of current systems . However, in the future, it is possible to to build the systems that can form representations about themselves. yes, a machine that have consciousness.

自我意识的AI：就目前的系统而言，这种AI有点过头了。 但是，将来有可能构建可以形成有关自身的表示形式的系统。 是的，一台有意识的机器。

To classify AI problems is using properties of the environments and components of the state that needs to be captured.

要对AI问题进行分类，是使用环境的属性和需要捕获的状态组件。

An environment can be fully observable when your agent can see the entire environment or partially observable like in serf driving car where you cant see the entire environment

当您的座席可以看到整个环境时，环境可以是完全可 观察的；例如，您不能看到整个环境的农奴驾驶汽车中， 部分可以观察到的环境

like palying chess game task where the agent can see the entire board, its fully observable.

就像在国际象棋游戏中，代理商可以看到整个棋盘一样，其完全可见。

It can be deterministic where an agent know for sure the result of each action it take or stochastic where an agent is not sure of the result of ist actions .

代理人肯定知道所采取的每个行动的结果是确定性的 ，或代理人不确定自己的行动的结果是随机的 。

for example Recognizing Handwritten Text task , the environment is stochastic becouse there are uncertainity about the result becouse there are number of possible solutions.

例如 识别手写文本任务时，环境是随机的，因为结果存在不确定性，因为存在许多可能的解决方案。

An environment can be discret where there is a finite number of actions you can take or continuous where the number of possible state is infinite .

在可能采取的动作数量有限的情况下，环境可以是离散的；在可能的状态数量为无限的情况下，环境可以是连续的。

like Playing Poker task , it is discret becouse there are finite number of actions an agent can take.

就像玩扑克任务一样，因为那里是离散的 代理可以采取的行动数量有限。

It can be benign where the agent t is the only one taking actions that intentionally affect its goal . or it could be adversarial where there are one or more agents that takes actions to defaeat its goal.

代理商t是唯一有意地影响其目标的行为可能是良性的。 或者，如果有一个或多个采取行动破坏其目标的行动者，可能是对抗性的 。

for example like playing chess task , it is adverserial becouse the agent is playing against another oponent who is taking actions to defeat the agent.

例如，像下棋任务，这是不利的，因为特工正在与采取行动击败特工的另一对手竞争。

In all this, what’s AI?

在所有这一切中，什么是AI？

An intelligence system is the one that takes action to maximize its chance to achieve the desired goal , that means it requires agent to behave optimally however it is hard to find optimal solution given the constraight the agent might face like for example a partialy observable environment , limited computational resources such as memories and processing speed .

情报系统是一种采取行动以最大化其实现预期目标机会的系统，这意味着它需要行动者表现最佳，但是考虑到行动者可能面对的局面，例如局部观察环境，很难找到最佳解决方案，有限的计算资源，如内存和处理速度。

intelligent Agent should not be expected to behave optimally but for the sake of quantifying our agent intelligence, we can come up with a level of performance or bound that we desire our agent to meet or exceed. for example we might want our flight planning agent to minimize the cost 30% or so . This known as bounded optimality .

不应期望智能代理的行为达到最佳状态，但是为了量化我们的代理智能，我们可以提出我们希望代理达到或超过的性能水平或界限。 例如，我们可能希望我们的飞行计划代理将成本降低30％左右。 这称为有界最优性。

to me AI is a branch of computer science concerned with building intelligent machine that perform intelligent tasks.

对我而言，人工智能是计算机科学的一个分支，与构建执行智能任务的智能机器有关。