artificial intelligence

Establish Transportation: Create a Road Using Cubic Spline Interpolation.Under normal driving conditions,All vehicle buckets are placed on a two-dimensional curve..This curve definesXzPrecise routes for plane driving.We useHermiteCurve as our

When I see this story about the voice of the little girl's guest, please do not think it is a famous man's story or a strange story. It is a book about the management issues and experiences of graphic cases generated thirty years ago. Its original

Is Robots a single individual or a unified spirit? Unlike "I Robot", robots in this film have their own personalities. The rule of the highest-leader machine is totally indecisive. In I robot, only the occasional variation of a robot gives the

Physics teachers in high school often think that problems given as text are more demanding than pure computations. After all, the pupils have to read and understand the problem first! So they don't state a problem like ''U = 10 V, I = 5A, P =? "But

?? In the local search algorithm, we no longer care about the path from the initial node to the target node, but consider moving from the current node to its neighboring state until it reaches a reasonable target state. Compared with the

1. About activating functions If according to the idea of the previous article, AI can not simulate the curve equation, such as the parabolic equation, in time to add more parameter values, also can not achieve the effect, so need to introduce

I've been having some trouble with my CNN network lately. Use C + + to write directly from scratch, in accordance with the hierarchical modularization. To do after the massive dynamic incremental learning of CNN. Write code, debugging, the results

Original address: http://www.sohu.com/a/151556765_642762 Recently, by Ipfconline in the elimination of the main well-known AI organizations, such as IBM, Microsoft, NVIDIA, Google, Amazon,elon Musk/spacex ... After the Twitter accounts of reputable

1. Main ideas: First of all, find a way to find a point, a right point to go over, and then reach the demand for road. Here, there are 3 properties for each point: The F,G,H.H is the estimated consumption of the current point to reach the endpoint,

Four, handle mouse events '***************************************************************************** ' * * Module name: Themousedown '** ' * * Description: This function mainly implements the following functions: ' * * 1. Determines whether the

first, the purpose of the experiment: To solve the problem of eight queens with backtracking method. second, the experimental content: 1, read the C language writing backtracking method to solve the eight Queen problem code. 2, reference C language

Using state space method to solve eight digital problems (4 UI) First, the experimental requirements Eight digital puzzle is also called nine problem, it is in the 3x3 checkered checkerboard, respectively placed table has the number 1, 2, 3, 4, 5, 6

650) this.width=650; "src=" Http://img.mp.itc.cn/upload/20160614/d772cb5e5a0442ab94136bed1b9adbac_th.jpg "style=" border:0px;margin:0px;padding:0px;font-size:0px; "/>　　Wen/Sindongfang, Gen Y author, columnist, Focus on the Internet technology fieldThe development of the term "artificial intelligence" has now gone through more than 60 spring and autumn. During the period, the

Recently in the study of Artificial neural network (Artificial neural netwroks), make notes, organize ideas Discrete single output perceptron algorithm, the legendary MP Two-valued Network: The value of the independent variable and its function, the value of the vector component only takes 0 and 1 functions, vectors Weight vector: w= (W1,W2,W3.....WN) Input vector: x= (X1,X2,X3.....XN) Training Sample

Sample program download: http://files.cnblogs.com/gpcuster/ANN1.rarIf you have any questions, refer to the FAQ first.If you do not find a satisfactory answer, you can leave a message below :)1 IntroductionI still remember hearing from senior students about Ann (Artificial Neural Network) when I first came into contact with RoboCup two years ago. This is amazing, he can learn to solve some problems well. Just like our people, we can learn and learn new

1 Introduction Remember when I first contacted RoboCup 2 years ago, I heard from my seniors that Ann (artificial neural network), this thing can be magical, he can learn to do some problems well enough to deal with. Just like us, we can learn new knowledge by studying. But for 2 years, I've always wanted to learn about Ann, but I haven't been successful. The main reason for this is that the introduction of this technology in our domestic tutorials i

Example of an artificial neural network algorithm implemented by Python [Based on the back propagation algorithm], python Artificial Neural Network This example describes the artificial neural network algorithm implemented by Python. We will share this with you for your reference. The details are as follows: Note: This program is written in Python3. You need to i

This is an extension of the discrete single output perceptron algorithm Related symbolic definitions refer to the artificial neural network (Artificial neural netwroks) Note-discrete single output perceptron algorithm Ok,start our Game 1. Initialization weight matrix W; 2. Repeat the following process until the training is complete: 2.1 For each sample (X,y), repeat the following procedure: 2.1.1 Inpu

In the previous article "Artificial Neural Network (Artificial neural netwroks) Notes-Eliminate the sample order of the BP algorithm" to modify the weight of the method is called the "steepest descent method." Every time the weight of the changes are determined, the weight will be modified. Even to the simplest single layer perceptron. But we have a question, whether every time the weight modification is g

1 Introduction An XOR operation is a commonly used calculation in a computer: 0 XOR 0 = 0 0 XOR 1 = 1 1 XOR 0 = 1 1 XOR 1 = 0 We can use the code in the first article to calculate this result Http://files.cnblogs.com/gpcuster/ANN1.rar (need to modify the training set), we can find that the results of learning does not satisfy us, because the single layer of neural network learning ability is limited , you need to use more complex networks to learn. In this article, we will use a new multi