artificial-intelligence

问题 I\'m new to neural networks/machine learning/genetic algorithms, and for my first implementation I am writing a network that learns to play snake (An example in case you haven\'t played it before) I have a few questions that I don\'t fully understand: Before my questions I just want to make sure I understand the general idea correctly. There is a population of snakes, each with randomly generated DNA. The DNA is the weights used in the neural network. Each time the snake moves, it uses the

问题 I have recently stumbled upon the game 2048. You merge similar tiles by moving them in any of the four directions to make \"bigger\" tiles. After each move, a new tile appears at random empty position with a value of either 2 or 4 . The game terminates when all the boxes are filled and there are no moves that can merge tiles, or you create a tile with a value of 2048 . One, I need to follow a well-defined strategy to reach the goal. So, I thought of writing a program for it. My current

问题 I\'m aware of the Gradient Descent and the Back-propagation Theorem. What I don\'t get is: When is using a bias important and how do you use it? For example, when mapping the AND function, when I use 2 inputs and 1 output, it does not give the correct weights, however, when I use 3 inputs (1 of which is a bias), it gives the correct weights. 回答1: I think that biases are almost always helpful. In effect, a bias value allows you to shift the activation function to the left or right , which may

问题 Please I am a bit new to Python and it has been nice, I could comment that python is very sexy till I needed to shift content of a 4x4 matrix which I want to use in building a 2048 game demo of the game is here I have this function def cover_left(matrix): new=[[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0]] for i in range(4): count=0 for j in range(4): if mat[i][j]!=0: new[i][count]=mat[i][j] count+=1 return new This is what this function does if you call it like this cover_left([ [1,0,2,0], [3,0,4