⼈⼯智能解决的问题_⼈⼯智能中的问题解决
⼈⼯智能解决的问题
The aim of is to develop a system which can solve the various problems on its own. But the challenge is, to understand a problem, a system must predict and convert the problem in its understandable form. That is, when an confronts a problem, it should first n the problem, and this information that the agent gets through the nsing should be converted into machine-understandable form. For this, a particular quence should be followed by the agent in which a particular format for the reprentation of agent's knowledge is defined and each time a problem aris, the agent can follow that particular approach to find a solution to it.
approach to find a solution to it
的⽬的是开发⼀种可以⾃⾏解决各种问题的系统。 但是挑战在于，要理解问题，系统必须以可理解的形式预测并转换问题。 就是说，当⼀个遇到问题时，它应该⾸先感知该问题，并且该代理通过感知获得的信息应转换为机器可理解的形式。 为此，代理应该遵循特定的顺序，
⽅法来找到解决⽅案 。
在该顺序中定义了⽤于表⽰代理知识的特定格式，并且每次出现问题时，代理都可以遵循该特定⽅法来找到解决⽅案
The steps involved in solving a problem
steps involved in solving a problem (by an ) are:
步骤是：
涉及的步骤
解决问题
解决问题 (通过的 )所涉及
1) Define a problem
1)定义⼀个问题
Whenever a problem aris, the agent must first define a problem to an extent so that a particular state space can be reprented through it. Analyzing and defining the problem is a very important st
ep becau if the problem is understood something which is different than the actual problem, then the whole problem-solving process by the agent is of no u.
每当出现问题时，代理必须⾸先将问题定义到⼀定程度，以便可以通过它表⽰特定的状态空间。 分析和定义问题是⾮常重要的⼀步，因为如果理解问题与实际问题有所不同，那么座席解决问题的整个过程将毫⽆⽤处。
2) Form the state space
2)形成状态空间
Convert the problem statement into state space. A state space is the collection of all the possible valid states that an agent can reside in. But here, all the possible states are chon which can exist according to the current problem. The rest are ignored while dealing with this particular problem.
将问题陈述转换为状态空间。 状态空间是代理可以驻留的所有可能有效状态的集合。但是在这⾥，根据当前问题选择可以存在的所有可能状态。 在处理此特定问题时，将忽略其余部分。
3) Gather knowledge
3)收集知识
collect and isolate the knowledge which is required by the agent to solve the current problem. This knowledge gathering is done from both the pre-embedded knowledge in the system and the knowledge it has gathered through the past experiences in solving the same type of problem earlier.
收集并隔离代理解决当前问题所需的知识。 知识的收集既可以从系统中预先嵌⼊的知识中进⾏，也可以通过它在解决早期类型问题时的过去经验中收集⽽来。
4) Planning-(Decide data structure and control strategy)
4)规划-(确定数据结构和控制策略)
A problem may not always be an isolated problem. It may contain various related problems as well or some related areas where the decision made with respect to the current problem can affect tho areas. So, a well-suited data structure and a relevant control strategy must be decided before attempting to solve the problem.
问题不⼀定总是孤⽴的问题。 它也可能包含各种相关问题，或者某些与当前问题有关的决策可能影响这些领域的相关领域。 因此，在尝试解决该问题之前，必须确定合适的数据结构和相关的控制策略。
5) Applying and executing
5)应⽤和执⾏
After all the gathering of knowledge and planning the strategies, the knowledge should be applied and the plans should be executed in a systematic way so s to reach the goal state in the most efficient and fruitful manner.
在所有知识的收集和战略计划之后，应该应⽤知识并以系统的⽅式执⾏计划，从⽽以最有效和富有成果的⽅式达到⽬标状态。
⼈⼯智能解决的问题
