We call ourselves Homo sapiens—man the wise—because our intelligence is so important to us. For thousands of years, we have tried to understand how we think; that is, how a mere handful of matter can perceive, understand, predict, and manipulate a world far larger and more complicated than itself. The field of artificial intelligence, or AI, goes further still: it attempts not just to understand but also to build intelligent entities.

Artificial-Intelligence-A-Modern-Approach-3rd-Edition

Paradigms-of-Artificial-Intelligence-Programming.p

Python中的群智能（遗传算法，粒子群优化，模拟退火，蚁群算法，免疫算法，Python中的人工鱼群算法） 文档： : 文档： : 源代码： : 帮助我们改善scikit-opt 安装 pip install scikit-opt 对于当前的开发人员版本： git clone git@github.com:guofei9987/scikit-opt.git cd scikit-opt pip install . 特征 功能1：UDF UDF （用户定义的函数）现在可用！ 例如，您刚刚制定了一种新型的selection功能。 现在，您的selection功能如下所示： ->演示代码： # step1: define your own operator: def selection_tournament ( algorithm , tourn_size ): Fi

人工智能简述 ARTIFICIAL INTELLIGENCE

Lisp in a Box for Windows Lisp in a Box on Windows has been modularized! •First, download the base installer and run it. This gives you GNU Emacs 21.3 and SLIME 2004-06-26. •Next, choose an implementation's module, and install it: ◦CLISP module. Includes CLISP 2.33. ◦Allegro Trial Edition 6.2 module. You must first install the trial edition from Franz's website. ◦Allegro 6.2 module. For people who have Allegro Common Lisp Enterprise Edition 6.2 already. •More than one implementation module can be installed.

Artificial Intelligence in Financial Markets: Cutting Edge Applications for Risk Management, Portfolio Optimization and Economics (New Developments in Quantitative Trading and Investment) 2017 | ISBN: 1137488794 | English | 344 pages | PDF | 8 MB As technology advancement has increased, so to have computational applications for forecasting, modelling and trading financial markets and information, and practitioners are finding ever more complex solutions to financial challenges. Neural networking is a highly effective, trainable algorithmic approach which emulates certain aspects of human brain functions, and is used extensively in financial forecasting allowing for quick investment decision making. This book presents the most cutting-edge artificial intelligence (AI)/neural networking applications for markets, assets and other areas of finance. Split into four sections, the book first explores time series analysis for forecasting and trading across a range of assets, including derivatives, exchange traded funds, debt and equity instruments. This section will focus on pattern recognition, market timing models, forecasting and trading of financial time series. Section II provides insights into macro and microeconomics and how AI techniques could be used to better understand and predict economic variables. Section III focuses on corporate finance and credit analysis providing an insight into corporate structures and credit, and establishing a relationship between financial statement analysis and the influence of various financial scenarios. Section IV focuses on portfolio management, exploring applications for portfolio theory, asset allocation and optimization. This book also provides some of the latest research in the field of artificial intelligence and finance, and provides in-depth analysis and highly applicable tools and techniques for practitioners and researchers in this field.

Lambda网络-Pytorch λ网络的实现，这是ImageNet上达到SOTA的一种新的图像识别方法。 新方法利用λ层，该层通过将上下文转换为称为lambda的线性函数并将这些线性函数分别应用于每个输入来捕获交互。 安装 $ pip install lambda-networks 用法 全球背景 import torch from lambda_networks import LambdaLayer layer = LambdaLayer ( dim = 32 , # channels going in dim_out = 32 , # channels

This book explains why AI is unique, what legal and ethical problems it could cause, and how we can address them. It argues that AI is unlike is any other previous technology, owing to its ability to take decisions independently and unpredictably. This gives rise to three issues: responsibility―who is liable if AI causes harm; rights―the disputed moral and pragmatic grounds for granting AI legal personality; and the ethics surrounding the decision-making of AI. The book suggests that in order to address these questions we need to develop new institutions and regulations on a cross-industry and international level. Incorporating clear explanations of complex topics, Robot Rules will appeal to a multi-disciplinary audience, from those with an interest in law, politics and philosophy, to computer programming, engineering and neuroscience.

两个法国RL大牛所写的经典强化学习Tutorial，算法理论介绍相当严格，文献总结全面