artificial-intelligence

Can someone explain in very simple words what it is. Also provide an example. So for example if u have to find the heuristic function of something how is it supposed to look like? Take as an example the problem: For the water jug problem http://www.math.tamu.edu/~dallen/hollywood/diehard/diehard.htm Devise and explain an admissible heuristic function (h) [not the trivial h(n) = 0]. The cost of an action is defined as 1 unit for performing the action, an additional 1 unit for moving each gallon of water (fill, empty, pour), and an additional 1 unit for wasting each gallon of water (empty). The

I am trying to implement an application that uses AdaBoost algorithm. I know that AdaBoost uses set of weak classifiers, but I don't know what these weak classifiers are. Can you explain it to me with an example and tell me if I have to create my own weak classifiers or I'm suppoused to use some kind of algorithm? marc_ferna When I used AdaBoost, my weak classifiers were basically thresholds for each data attribute. Those thresholds need to have a performance of more than 50%, if not it would be totally random. Here is a good presentation about Adaboost and how to calculate those weak

I have a question regarding Genetic Programming. I am going to work on a genetic algorithm for a game called Battleships . My question is: How would I decide upon a "decision" model for the AI to evolve? And how does that work? I have read multiple papers and multiple answers that just speak about using different models, but could not find something specific, which, unfortunately, I apparently need to wrap my head around the problem. I want it to evolve over multiple iterations and "learn" what works best, but not sure how to save these "decisions" (I know to a file, but "encoded" how?) in a

I want know which programming language provides good number of libraries to program a web bot? Something like crawling a web page for data. Say I want fetch weather for weather.yahoo.com website. Also will the answer be same for a AI desktop bot? Here is how you could do it in Python: from urllib2 import urlopen from BeautifulSoup import BeautifulSoup soup=BeautifulSoup(urlopen("http://weather.yahoo.com/").read()) for x in soup.find(attrs={"id":"myLocContainer"}).findAll("li"): print x.a["title"], x.em.contents Prints: Full forecast for Chicago, Illinois, United States (Haze) [u'35...47 °F']

I am currently implementing something quite similar to checkers. So, I have this table game and there are both white and black pieces. Where there are neither white or black pieces, you dno't have pieces. I'm currently doing the GetValidMoves() method that'll return all the current moves one can do with the current board. I am thus wondering what might be the best way to represent the board. The naive approach would be to have a matrix with 0's 1's and 2's (for no piece, white piece and black piece). Other idea would be to instead of a matrix representation of the board, have 2 lists(or any

I am trying to create my own loss function: def custom_mse(y_true, y_pred): tmp = 10000000000 a = list(itertools.permutations(y_pred)) for i in range(0, len(a)): t = K.mean(K.square(a[i] - y_true), axis=-1) if t < tmp : tmp = t return tmp It should create permutations of predicted vector, and return the smallest loss. "`Tensor` objects are not iterable when eager execution is not " TypeError: `Tensor` objects are not iterable when eager execution is not enabled. To iterate over this tensor use `tf.map_fn`. error. I fail to find any source for this error. Why is this happening? Thanks for hel.