artificial-intelligence

问题 I have made a puzzle where the player slides blocks around to goals - the rules are fairly simple: Only one slider block may move at a time The object is to move the slider blocks into goal nodes - you only need to fill the goal nodes, not necessarily get all slider blocks into the goal nodes. If the slider block slides on ice, it will continue moving in that direction until it is stopped or moved If the slider block hits something solid (concrete, another block) it stops and can be moved

问题 I have this image How to OCR it? I know this is very challenging, but I would really appreciate any help. 回答1: If you have the time to develop the detection yourself, I would do it roughly like this: Get 1000 images or so and either OCR them yourself or let the people on Amazon Mechanical Turk do it for you, it will cost virtually nothing. Now you have something to tune your algorithm on and measure how well you are doing. Like Ryan wrote, play with standard image filters, contrast, color,

问题 I'm working on a 2D game that has a huge amount of dynamic entities. For fun's sake, let's call them soldiers, and let's say there are 50000 of them (which I just randomly thought up, it might be much more or much less :)). All these soldiers are moving every frame according to rules - think boids / flocking / steering behaviour. For each soldier, to update it's movement I need the X soldiers that are closest to the one I'm processing. What would be the best spatial hierarchy to store them to

问题 For my graduate research I am creating a neural network that trains to recognize images. I am going much more complex than just taking a grid of RGB values, downsampling, and and sending them to the input of the network, like many examples do. I actually use over 100 independently trained neural networks that detect features, such as lines, shading patterns, etc. Much more like the human eye, and it works really well so far! The problem is I have quite a bit of training data. I show it over

问题 I read a few books and articles about Convolutional neural network, it seems I understand the concept but I don't know how to put it up like in image below: (source: what-when-how.com) from 28x28 normalized pixel INPUT we get 4 feature maps of size 24x24. but how to get them ? resizing the INPUT image ? or performing image transformations? but what kind of transformations? or cutting the input image into 4 pieces of size 24x24 by 4 corner? I don't understand the process, to me it seem they

问题 I am currently working on a neural network based approach to short document classification, and since the corpuses I am working with are usually around ten words, the standard statistical document classification methods are of limited use. Due to this fact I am attempting to implement some form of automated synonym detection for the matches provided in the training. My question more specifically is about resolving a situation as follows: Say I have classifications of "Involving Food", and one

问题 Hi I'm pretty new to Python and to NLP. I need to implement a perceptron classifier. I searched through some websites but didn't find enough information. For now I have a number of documents which I grouped according to category(sports, entertainment etc). I also have a list of the most used words in these documents along with their frequencies. On a particular website there was stated that I must have some sort of a decision function accepting arguments x and w. x apparently is some sort of

问题 In my text book I noticed that both these algorithms work almost exactly the same, I am trying to understand what's the major difference between them . The textbook traversed this example using A* the same way it did with best-first search . Any help would be appreciated. 回答1: Best-first search algorithm visits next state based on heuristics function f(n) = h with lowest heuristic value (often called greedy). It doesn't consider cost of the path to that particular state. All it cares about is

问题 Suggest an algorithm and data structure for solving the game Globs (http://www.deadwhale.com/play.php?game=131). It's pretty fun in a geeky kind of way. State the time-space complexity (big-O) of your approach in terms of N , the size of the grid (N>=14). Good-enough efficient algorithms with low complexity are preferred. (MatrixFrog correctly points out this game is also known as FloodIt, and Smashery gave a solution 3 months ago in the link he cites below. All you dudes suggesting pruning

问题 I want to program a chess engine which learns to make good moves and win against other players. I've already coded a representation of the chess board and a function which outputs all possible moves. So I only need an evaluation function which says how good a given situation of the board is. Therefore, I would like to use an artificial neural network which should then evaluate a given position. The output should be a numerical value. The higher the value is, the better is the position for the