数学代写| Logic and AI 离散代考
离散数学在计算领域有广泛的应用，例如密码学、编码理论、 形式方法, 语言理论, 可计算性, 人工智能, 理论 数据库和软件的可靠性。 离散数学的重点是理论和应用，而不是为了数学本身而研究数学。 一切算法的基础都是离散数学一切加密的理论基础都是离散数学
编程时候很多奇怪的小技巧（特别是所有和位计算相关的东西）核心也是离散数学
其他相关科目课程代写：组合学Combinatorics集合论Set Theory概率论Probability组合生物学Combinatorial Biology组合化学Combinatorial Chemistry组合数据分析Combinatorial Data Analysis
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离散数学代写
The long-term goal of Artificial Intelligence is to create a thinking machine that is intelligent, has consciousness, has the ability to learn, has free will and is ethical. Artificial Intelligence is a young field and John McCarthy and others coined the term in 1956. Alan Turing devised the Turing Test in the early 1950s as a way to determine whether a machine was conscious and intelligent. Turing believed that machines would eventually be developed that would stand a good chance of passing the ‘Turing Test’.
There are deep philosophical problems in Artificial Intelligence, and some researchers believe that its goals are impossible or incoherent. Even if Artificial Intelligence is possible, there are moral issues to consider such as the exploitation of artificial machines by humans and whether it is ethical to do this. Weizenbaum argues that AI is a threat to human dignity, and that AI should not replace humans in positions that require respect and care.
John McCarthy has long advocated the use of logic in AI, and mathematical logic has been used in the AI field to formalize knowledge and in guiding the design of mechanized reasoning systems. Logic has been used as an analytic tool, as a knowledge representation formalism and as a programming language John McCarthy has 1 logic has been used in design of mechanized reaso as a knowledge repres (Fig. 16.6).
McCarthy’s long-term goal was to formalize common-sense reasoning, i.e. the normal reasoning that is employed in problem-solving and dealing with normal events in the real world. McCarthy [6] argues that it is reasonable for logic to play a key role in the formalization of common-sense knowledge, and this includes the formalization of basic facts about actions and their effects, facts about beliefs and common-sense problems to be solved by logical reasoning.
common-sense problems to be solved by logical reasoning. Its formalization requires sufficient understanding of the common-sense world, and often the relevant facts to solve a particular problem are unknown. It may be have millions of facts stored in its memory, and the problem is how to determine which of these should be chosen from its memory to serve as premises in logical deduction.
McCarthy’s influential 1959 paper discusses various common-sense problems such as getting home from the airport. Mathematical logic is the standard approach to express premises, and it includes rules of inferences that are used to deduce valid conclusions from a set of premises. Its rigorous deductive reasoning shows how new formulae may be logically deduced from a set or premises.
McCarthy’s approach to programs with common sense has been criticized by Bar-Hillel and others on the grounds that common sense is fairly elusive, and the difficulty that a machine would have in determining which facts are relevant to a particular deduction from its known set of facts. However, McCarthy’s approach has showed how logical techniques can contribute to the solution of specific AI problems.
图论代考
人工智能的长期目标是创造一个智能的、有意识的、有学习能力的、有自由意志的、有道德的思考机器。人工智能是一个年轻的领域，约翰麦卡锡和其他人在 1956 年创造了这个术语。艾伦图灵在 1950 年代初期设计了图灵测试，作为确定机器是否有意识和智能的一种方法。图灵相信最终会开发出很有可能通过“图灵测试”的机器。
人工智能存在深刻的哲学问题，一些研究人员认为其目标是不可能的或不连贯的。即使人工智能是可能的，也有道德问题需要考虑，例如人类对人工机器的利用以及这样做是否合乎道德。 Weizenbaum 认为，人工智能是对人类尊严的威胁，人工智能不应取代人类担任需要尊重和关怀的职位。
John McCarthy 长期以来一直提倡在 AI 中使用逻辑，并且数理逻辑已在 AI 领域用于形式化知识和指导机械化推理系统的设计。逻辑已被用作分析工具、知识表示形式和编程语言 John McCarthy 1 逻辑已被用于设计机械化原因作为知识表示（图 16.6）。
麦卡锡的长期目标是将常识推理形式化，即用于解决问题和处理现实世界中正常事件的正常推理。 McCarthy [6] 认为逻辑在常识知识的形式化中起关键作用是合理的，这包括关于行动及其影响的基本事实、关于信念的事实和待解决的常识问题的形式化。通过逻辑推理。
通过逻辑推理来解决的常识性问题。它的形式化需要对常识世界有足够的了解，而且解决特定问题的相关事实通常是未知的。它可能有数百万个事实存储在它的内存中，问题是如何确定应该从它的内存中选择哪些作为逻辑推理的前提。
麦卡锡在 1959 年发表的有影响力的论文讨论了各种常识性问题，例如从机场回家。数理逻辑是表达前提的标准方法，它包括用于从一组前提推导出有效结论的推理规则。其严格的演绎推理显示了如何从一个集合或前提逻辑推导出新的公式。
Bar-Hillel 和其他人批评了麦卡锡对具有常识的程序的方法，理由是常识相当难以捉摸，并且机器很难从已知的一组事实中确定哪些事实与特定的推论相关。 .然而，McCarthy 的方法展示了逻辑技术如何有助于解决特定的 AI 问题。
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抽象代数代考
抽象代数就是一门概念繁杂的学科，我们最重要的一点我想并不是掌握多少例子。即便是数学工作者也不会刻意记住Jacobson环、正则环这类东西，重要的是你要知道这门学科的基本工具和基本手法，对概念理解了没有，而这一点不需要用例子来验证，只需要看看你的理解和后续概念是否相容即可。
矩阵论代考matrix theory
数学，矩阵理论是一门研究矩阵在数学上的应用的科目。矩阵理论本来是线性代数的一个小分支，但其后由于陆续在图论、代数、组合数学和统计上得到应用，渐渐发展成为一门独立的学科。
密码学代考
密码学是研究编制密码和破译密码的技术科学。 研究密码变化的客观规律，应用于编制密码以保守通信秘密的，称为编码学；应用于破译密码以获取通信情报的，称为破译学，总称密码学。 电报最早是由美国的摩尔斯在1844年发明的，故也被叫做摩尔斯电码。
- Cryptosystem
- A system that describes how to encrypt or decrypt messages
- Plaintext
- Message in its original form
- Ciphertext
- Message in its encrypted form
- Cryptographer
- Invents encryption algorithms
- Cryptanalyst
- Breaks encryption algorithms or implementations
编码理论代写
编码理论（英语：Coding theory）是研究编码的性质以及它们在具体应用中的性能的理论。编码用于数据压缩、加密、纠错，最近也用于网络编码中。不同学科（如信息论、电机工程学、数学、语言学以及计算机科学）都研究编码是为了设计出高效、可靠的数据传输方法。这通常需要去除冗余并校正（或检测）数据传输中的错误。
编码共分四类：[1]
数据压缩和前向错误更正可以一起考虑。
