网站首页 软件下载 游戏下载 翻译软件 电子书下载 电影下载 电视剧下载 教程攻略
| 书名 | 人工智能(英文版)/国外计算机科学教材系列 |
| 分类 | |
| 作者 | (美)琼斯 |
| 出版社 | 电子工业出版社 |
| 下载 |  |
| 简介 | 编辑推荐 本书为广大学生和人工智能开发人员提供了学习人工智能相关概念的一种新思路。 书中包含人工智能在多个领域的许多最新应用，这些领域包括游戏程序设计、群体智能、智能Agent、神经网络、人工免疫系统、遗传算法、模式识别、数值优化以及数据挖掘等。本书还讨论了从早期的LISP语言到近期的Python语言等多种人工智能语言。书中不仅包括了人工智能的理论和主要课题，还介绍了从数据输入到转换再到数据输出（即算法的使用）的实际需要的信息。因为传统的人工智能概念目前仅仅表示算法的各种类型，因此需要用一种不同的方法来介绍人工智能算法。这种“传感器－算法－效应器”的方法为这些算法提供了一个基础环境，能够帮助学生和人工智能从业者更好地理解它们，从而更好地应用这些算法。 内容推荐 本书包含当前人工智能（AI）研究的主要内容，尤其强调实际应用，涉及数据挖掘等许多最新应用领域。全书共13章，分别讲述了AI的历史、不用知识的搜索、用知识的搜索、AI与博弈、知识表示、机器学习、演化计算、神经网络I、机器人学与AI、智能Agent、来自生物的模型与混合模型以及AⅡ语言。本书给出了算法的较详细实现，与现有的以理论基础为核心的大多数经典人工智能著作相比，本书有自身的鲜明特色，且内容与国内人工智能课程的教学内容吻合，尤其有利于培养学生解决人工智能实际问题的能力。 本书适合高等学校计算机、自动化等信息学科的本科生和研究生阅读，也适合广大人工智能爱好者自学使用，本书也能为人工智能研究人员了解各种算法的设计思路和具体实现框架提供参考。 目录 Chapter 1 The History of AI What is Intelligence? The Search for Mechanical Intelligence The Very Early Days(the early 1950s) Artificial Intelligence Emerges as a Field AI's Winter AI Re-emerges AI Inter-Disciplinary R&D Systems Approach Overview of this Book Chapter Summary References Resources Exercises Chapter 2 Uninformed Search Search and AI Classes of Search General State Space Search Trees, Graphs, and Representation Uninformed Search Improvements Algorithm Advantages Chapter Summary Algorithms Summary References Exercises Chapter 3 Informed Search Informed Search Best-First Search(Best-FS) A* Search Hill-Climbing Search Simulated Annealing(SA) Tabu Search Constraint Satisfaction Problems(CSP) Constraint Satisfaction Algorithms Chapter Summary Algorithms Summary References Resources Exercises Chapter 4 AI and Games Two-Player Games The Minimax Algorithm Classical Game AI Video Game AI Chapter Summary References Resources Exercises Chapter 5 Knowledge Representation Introduction Types of Knowledge The Role of Knowledge Semantic Networks Frames Propositional Logic First-Order Logic(Predicate Logic) Semantic Web Computational Knowledge Discovery Ontology Communication of Knowledge Chapter Summary References Resources Exercises Chapter 6 Machine Learning Machine-Learning Algorithms Chapter Summary Resources Exercises Chapter 7 Evolutionary Computation Short History of Evolutionary Computation Biological Motivation Genetic Algorithms (GA) Genetic Programming (GP) Evolutionary Strategies (ES) Differential Evolution (DE) Particle Swarm Optimization (PSO) Evolvable Hardware Chapter Summary References Resources Exercises Chapter 8 Neural Networks I Short History of Neural Networks Biological Motivation Fundamentals of Neural Networks The Perceptron Least-Mean-Square (LMS) Learning Learning with Backpropagation Probabilistic Neural Networks (PNN) Other Neural Network Architectures Tips for Building Neural Networks Chapter Summary References Exercises Chapter 9 Neural Networks II Unsupervised Learning Hebbian Learning Simple Competitive Learning K-Means Clustering Adaptive Resonance Theory (ART) Hopfield Auto-Associative Model Chapter Summary References Exercises Chapter 10 Robotics and AI Introduction to Robotics Braitenburg Vehicles Natural Sensing and Control Perception with Sensors Actuation with Effectors Robotic Control Systems Simple Control Architectures Movement Planning Group or Distributed Robotics Robot Programming Languages Robot Simulators Chapter Summary References Resources Exercises Chapter 11 Intelligent Agents Anatomy of an Agent Agent Properties and AI Agent Environments Agent Taxonomies Agent Architectures Agent Languages Agent Communication ACL (FIPA Agent Communication Language) Chapter Summary Resources References Exercises Chapter 12 Biologically Inspired and Hybrid Models Cellular Automata (CA) Artificial Immune Systems Artificial Life Fuzzy Systems Evolutionary Neural Networks Ant Colony Optimization (ACO) Affective Computing Resources Chapter 13 The Languages of AI Language Taxonomy Languages of AI Other Languages Chapter Summary References Resources Exercises |
| 随便看 |
|
霍普软件下载网电子书栏目提供海量电子书在线免费阅读及下载。