The book covers the most recent developments in machine learning, signal analysis, and their applications. It covers the topics of machine intelligence such as: deep learning, soft computing approaches, support vector machines (SVMs), least square SVMs (LSSVMs) and their variants; and covers the topics of signal analysis such as: biomedical signals including electroencephalogram (EEG), magnetoencephalography (MEG), electrocardiogram (ECG) and electromyogram (EMG) as well as other signals such as speech signals, communication signals, vibration signals, image, and video. Further, it analyzes normal and abnormal categories of real-world signals, for example normal and epileptic EEG signals using numerous classification techniques. The book is envisioned for researchers and graduate students in Computer Science and Engineering, Electrical Engineering, Applied Mathematics, and Biomedical Signal Processing.

Artificial Intelligence foundations of computational agents AI经典、基础书籍

优化计算广泛应用于信息学科的各个研究领域，然而传统优化方法在实际应用中有很大的局限性。为了解决该问题，近年来，各种智能优化算法的研究得到了蓬勃发展，其中有广为人知的遗传算法、模拟退火算法、蚁群算法、神经网络算法等。迄今为止，智能优化算法在各个学科和各种实际应用场合中已经得到了广泛且有效的使用。本课程将紧密跟踪学术界最新发展动态，为信息学科的研究生掌握最新的智能优化技术抛砖引玉，为他们后续开展学术研究打下坚实基础。

很好的学习资料，中文英文都有，可以根据自己的情况学习

Robot Ethics 2.0 From Autonomous Cars to Artificial Intelligence 英文无水印原版pdf pdf所有页面使用FoxitReader、PDF-XChangeViewer、SumatraPDF和Firefox测试都可以打开 本资源转载自网络，如有侵权，请联系上传者或csdn删除 查看此书详细信息请在美国亚马逊官网搜索此书

Fundamentals of Computational Intelligence Keller 2016

Artificial Intelligence for Humans, Volume 1-2，包括AI基本算法，自然规律启发的算法以及深度学习

Artificial Intelligence for Robotics starts with an introduction to Robot Operating Systems (ROS), Python, robotic fundamentals, and the software and tools that are required to start out with robotics. You will learn robotics concepts that will be useful for making decisions, along with basic navigation skills. As you make your way through the chapters, you will learn about object recognition and genetic algorithms, which will teach your robot to identify and pick up an irregular object. With plenty of use cases throughout, you will explore natural language processing (NLP) and machine learning techniques to further enhance your robot. In the concluding chapters, you will learn about path planning and goal-oriented programming, which will help your robot prioritize tasks.

该资源是Prolog编程的介绍，可用于学习Prolog编程语言。

从获取数据，组织存储，到算法实现，加载运算，结果的分析利用演示