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  • chess AI for GAE

    - by Richard
    I am looking for a Chess AI that can be run on Google App Engine. Most chess AI's seem to be written in C and so can not be run on the GAE. It needs to be strong enough to beat a casual player, but efficient enough that it can calculate a move within a single request (less than 10 secs). Ideally it would be written in Python for easier integration with existing code. I came across a few promising projects but they don't look mature: http://code.google.com/p/chess-free http://mariobalibrera.com/mics/ai.html

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  • How to find minimum cut-sets for several subgraphs of a graph of degrees 2 to 4

    - by Tore
    I have a problem, Im trying to make A* searches through a grid based game like pacman or sokoban, but i need to find "enclosures". What do i mean by enclosures? subgraphs with as few cut edges as possible given a maximum size and minimum size for number of vertices that act as soft constraints. Alternatively you could say i am looking to find bridges between subgraphs, but its generally the same problem. Given a game that looks like this, what i want to do is find enclosures so that i can properly find entrances to them and thus get a good heuristic for reaching vertices inside these enclosures. So what i want is to find these colored regions on any given map. The reason for me bothering to do this and not just staying content with the performance of a simple manhattan distance heuristic is that an enclosure heuristic can give more optimal results and i would not have to actually do the A* to get some proper distance calculations and also for later adding competitive blocking of opponents within these enclosures when playing sokoban type games. Also the enclosure heuristic can be used for a minimax approach to finding goal vertices more properly. Do you know of a good algorithm for solving this problem or have any suggestions in things i should explore?

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  • Help with Neuroph neural network

    - by user359708
    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 100 examples of what a car looks like. Then 100 examples of what a person looks like. Then over 100 of what a dog looks like, etc. This is quite a bit of training data! Currently I am running at about one week to train the network. This is kind of killing my progress, as I need to adjust and retrain. I am using Neuroph, as the low-level neural network API. I am running a dual-quadcore machine(16 cores with hyperthreading), so this should be fast. My processor percent is at only 5%. Are there any tricks on Neuroph performance? Or Java peroformance in general? Suggestions? I am a cognitive psych doctoral student, and I am decent as a programmer, but do not know a great deal about performance programming.

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  • how to work with strings and integers as bit strings in python?

    - by Manuel
    Hello! I'm developing a Genetic Algorithm in python were chromosomes are composed of strings and integers. To apply the genetic operations, I want to convert these groups of integers and strings into bit strings. For example, if one chromosome is: ["Hello", 4, "anotherString"] I'd like it to become something like: 0100100100101001010011110011 (this is not actual translation). So... How can I do this? Chromosomes will contain the same amount of strings and integers, but this numbers can vary from one algorithm run to another. To be clear, what I want to obtain is the bit representation of each element in the chromosome concatenated. If you think this would not be the best way to apply genetic operators (such as mutation and simple crossover) just tell me! I'm open to new ideas. Thanks a lot! Manuel

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  • Quantum PSO and Charged PSO (PSO = Particle Swarm Optimizer)

    - by The Elite Gentleman
    Hi Guys I need to implement PSO's (namely charged and quantum PSO's). My questions are these: What Velocity Update strategy do each PSO's use (Synchronous or Asynchronous particle update) What social networking topology does each of the PSO's use (Von Neumann, Ring, Star, Wheel, Pyramid, Four Clusters) For now, these are my issues. All your help will be appreciated. Thanks.

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  • A* (A-star) implementation in AS3

    - by Bryan Hare
    Hey, I am putting together a project for a class that requires me to put AI in a top down Tactical Strategy game in Flash AS3. I decided that I would use a node based path finding approach because the game is based on a circular movement scheme. When a player moves a unit he essentially draws a series of line segments that connect that a player unit will follow along. I am trying to put together a similar operation for the AI units in our game by creating a list of nodes to traverse to a target node. Hence my use of Astar (the resulting path can be used to create this line). Here is my Algorithm function findShortestPath (startN:node, goalN:node) { var openSet:Array = new Array(); var closedSet:Array = new Array(); var pathFound:Boolean = false; startN.g_score = 0; startN.h_score = distFunction(startN,goalN); startN.f_score = startN.h_score; startN.fromNode = null; openSet.push (startN); var i:int = 0 for(i= 0; i< nodeArray.length; i++) { for(var j:int =0; j<nodeArray[0].length; j++) { if(!nodeArray[i][j].isPathable) { closedSet.push(nodeArray[i][j]); } } } while (openSet.length != 0) { var cNode:node = openSet.shift(); if (cNode == goalN) { resolvePath (cNode); return true; } closedSet.push (cNode); for (i= 0; i < cNode.dirArray.length; i++) { var neighborNode:node = cNode.nodeArray[cNode.dirArray[i]]; if (!(closedSet.indexOf(neighborNode) == -1)) { continue; } neighborNode.fromNode = cNode; var tenativeg_score:Number = cNode.gscore + distFunction(neighborNode.fromNode,neighborNode); if (openSet.indexOf(neighborNode) == -1) { neighborNode.g_score = neighborNode.fromNode.g_score + distFunction(neighborNode,cNode); if (cNode.dirArray[i] >= 4) { neighborNode.g_score -= 4; } neighborNode.h_score=distFunction(neighborNode,goalN); neighborNode.f_score=neighborNode.g_score+neighborNode.h_score; insertIntoPQ (neighborNode, openSet); //trace(" F Score of neighbor: " + neighborNode.f_score + " H score of Neighbor: " + neighborNode.h_score + " G_score or neighbor: " +neighborNode.g_score); } else if (tenativeg_score <= neighborNode.g_score) { neighborNode.fromNode=cNode; neighborNode.g_score=cNode.g_score+distFunction(neighborNode,cNode); if (cNode.dirArray[i]>=4) { neighborNode.g_score-=4; } neighborNode.f_score=neighborNode.g_score+neighborNode.h_score; openSet.splice (openSet.indexOf(neighborNode),1); //trace(" F Score of neighbor: " + neighborNode.f_score + " H score of Neighbor: " + neighborNode.h_score + " G_score or neighbor: " +neighborNode.g_score); insertIntoPQ (neighborNode, openSet); } } } trace ("fail"); return false; } Right now this function creates paths that are often not optimal or wholly inaccurate given the target and this generally happens when I have nodes that are not path able, and I am not quite sure what I am doing wrong right now. If someone could help me correct this I would appreciate it greatly. Some Notes My OpenSet is essentially a Priority Queue, so thats how I sort my nodes by cost. Here is that function function insertIntoPQ (iNode:node, pq:Array) { var inserted:Boolean=true; var iterater:int=0; while (inserted) { if (iterater==pq.length) { pq.push (iNode); inserted=false; } else if (pq[iterater].f_score >= iNode.f_score) { pq.splice (iterater,0,iNode); inserted=false; } ++iterater; } } Thanks!

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  • Entropy using Decision Tree's

    - by Matt Clements
    Train a decision tree on the data represented by attributes A1, A2, A3 and outcome C described below: A1 A2 A3 C 1 0 1 0 0 1 1 1 0 0 1 0 For log2(1/3) = 1.6 and log2(2/3) = 0.6, answer the following questions: a) What is the value of entropy H for the given set of training example? b) What is the portion of the positive samples split by attribute A2? c) What is the value of information gain, G(A2), of attribute A2? d) What is IFTHEN rule(s) for the decision tree?

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  • Update Rule in Temporal difference

    - by Betamoo
    The update rule TD(0) Q-Learning: Q(t-1) = (1-alpha) * Q(t-1) + (alpha) * (Reward(t-1) + gamma* Max( Q(t) ) ) Then take either the current best action (to optimize) or a random action (to explorer) Where MaxNextQ is the maximum Q that can be got in the next state... But in TD(1) I think update rule will be: Q(t-2) = (1-alpha) * Q(t-2) + (alpha) * (Reward(t-2) + gamma * Reward(t-1) + gamma * gamma * Max( Q(t) ) ) My question: The term gamma * Reward(t-1) means that I will always take my best action at t-1 .. which I think will prevent exploring.. Can someone give me a hint? Thanks

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  • Pong: How does the paddle know where the ball will hit?

    - by Roflcoptr
    After implementing Pacman and Snake I'm implementing the next very very classic game: Pong. The implementation is really simple, but I just have one little problem remaining. When one of the paddle (I'm not sure if it is called paddle) is controlled by the computer, I have trouble to position it at the correct position. The ball has a current position, a speed (which for now is constant) and a direction angle. So I could calculate the position where it will hit the side of the computer controlled paddle. And so Icould position the paddle right there. But however in the real game, there is a probability that the computer's paddle will miss the ball. How can I implement this probability? If I only use a probability of lets say 0.5 that the computer's paddle will hit the ball, the problem is solved, but I think it isn't that simple. From the original game I think the probability depends on the distance between the current paddle position and the position the ball will hit the border. Does anybody have any hints how exactly this is calculated?

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  • Prolog: Not executing code as expected.

    - by Louis
    Basically I am attempting to have an AI agent navigate a world based on given percepts. My issue is handling how the agent moves. Basically, I have created find_action/4 such that we pass in the percepts, action, current cell, and the direction the agent is facing. As it stands the entire code looks like: http://wesnoth.pastebin.com/kdNvzZ6Y My issue is mainly with lines 102 to 106. Basically, in it's current form the code does not work and the find_action is skipped even when the agent is in fact facing right (I have verified this). This broken code is as follows: % If we are headed right, take a left turn find_action([_, _, _, _, _], Action, _, right) :- retractall(facing(_)), assert(facing(up)), Action = turnleft . However, after some experimentation I have concluded that the following works: % If we are headed right, take a left turn find_action([_, _, _, _, _], Action, _, _) :- facing(right), retractall(facing(_)), assert(facing(up)), Action = turnleft . I am not entire sure why this is. I've attempted to create several identical find_action's as well, each checking a different direction using the facing(_) format, however swipl does not like this and throws an error. Any help would be greatly appreciated.

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  • Annoying Captcha >> How to programm a form that can SMELL difference between human and robot?

    - by Sam
    Hi folks. On the comment of my old form needing a CAPTHA, I felt I share my problem, perhaps you recognize it and find its time we had better solutions: FACTUAL PROBLEM I know most of my clients (typical age= 40~60) hate CAPTCHA things. Now, I myself always feel like a robot, when I have to sueeze my eyes and fill in the strange letters from the Capcha... Sometimes I fail! Go back etc. Turnoff. I mean comon its 2011, shouldnt the forms have better A.I. by now? MY NEW IDEA (please dont laugh) Ive thought about it and this is my idea's to tell difference between human and robot: My idea is to give credibility points. 100 points = human 0% = robot. require real human mouse movements require mousemovements that dont follow any mathematical pattern require non-instantaneous reading delays, between load and first input in form when typing in form, delays are measured between letters and words approve as human when typical human behaviour measured (deleting, rephrasing etc) dont allow instant pasting or all fields give points for real keyboard pressures retract points for credibility when hyperlinks in form Test wether fake email field (invisible by human) is populated (suggested by Tomalak) when more than 75% human cretibility, allow to be sent without captcha when less than 25% human crecibility, force captcha puzzle to be sure Could we write a A.I. PHP that replaces the human-annoying capthas, meanwhile stopping most spamservers filing in the data? Not only for the fun of it, but also actually to provide a 99% better alternative than CAPTHCA's. Imagine the userfriendlyness of your forms! Your site distinguishing itself from others, showing your audience your sites KNOWS the difference between a robot and a human. Imagine the advangage. I am trying to capture the essense of that distinguishing edge. PROGRAMMING QUESTION: 1) Are such things possible to programm? 2) If so how would you start such programm? 3) Are there already very good working solutions available elsewhere? 4) If it isn't so hard, your are welcome to share your answer/solutions below. 5) upon completion of hints and new ideas, could this page be the start of a new AI captcha, OR should I forget about it and just go with the flow, forget about the whole AI dream, and use captcha like everyone else.

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  • TicTacToe AI Making Incorrect Decisions

    - by Chris Douglass
    A little background: as a way to learn multinode trees in C++, I decided to generate all possible TicTacToe boards and store them in a tree such that the branch beginning at a node are all boards that can follow from that node, and the children of a node are boards that follow in one move. After that, I thought it would be fun to write an AI to play TicTacToe using that tree as a decision tree. TTT is a solvable problem where a perfect player will never lose, so it seemed an easy AI to code for my first time trying an AI. Now when I first implemented the AI, I went back and added two fields to each node upon generation: the # of times X will win & the # of times O will win in all children below that node. I figured the best solution was to simply have my AI on each move choose and go down the subtree where it wins the most times. Then I discovered that while it plays perfect most of the time, I found ways where I could beat it. It wasn't a problem with my code, simply a problem with the way I had the AI choose it's path. Then I decided to have it choose the tree with either the maximum wins for the computer or the maximum losses for the human, whichever was more. This made it perform BETTER, but still not perfect. I could still beat it. So I have two ideas and I'm hoping for input on which is better: 1) Instead of maximizing the wins or losses, instead I could assign values of 1 for a win, 0 for a draw, and -1 for a loss. Then choosing the tree with the highest value will be the best move because that next node can't be a move that results in a loss. It's an easy change in the board generation, but it retains the same search space and memory usage. Or... 2) During board generation, if there is a board such that either X or O will win in their next move, only the child that prevents that win will be generated. No other child nodes will be considered, and then generation will proceed as normal after that. It shrinks the size of the tree, but then I have to implement an algorithm to determine if there is a one move win and I think that can only be done in linear time (making board generation a lot slower I think?) Which is better, or is there an even better solution?

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  • whats the diference between train, validation and test set, in neural networks?

    - by Daniel
    Im using this library http://pastebin.com/raw.php?i=aMtVv4RZ to implement a learning agent. I have generated the train cases, but i dont know for sure what are the validation and test sets, the teacher says: 70% should be train cases, 10% will be test cases and the rest 20% should be validation cases. Thanks. edit i have this code, for training.. but i have no ideia when to stop training.. def train(self, train, validation, N=0.3, M=0.1): # N: learning rate # M: momentum factor accuracy = list() while(True): error = 0.0 for p in train: input, target = p self.update(input) error = error + self.backPropagate(target, N, M) print "validation" total = 0 for p in validation: input, target = p output = self.update(input) total += sum([abs(target - output) for target, output in zip(target, output)]) #calculates sum of absolute diference between target and output accuracy.append(total) print min(accuracy) print sum(accuracy[-5:])/5 #if i % 100 == 0: print 'error %-14f' % error if ? < ?: break

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  • Astar implementation in AS3

    - by Bryan Hare
    Hey, I am putting together a project for a class that requires me to put AI in a top down Tactical Strategy game in Flash AS3. I decided that I would use a node based path finding approach because the game is based on a circular movement scheme. When a player moves a unit he essentially draws a series of line segments that connect that a player unit will follow along. I am trying to put together a similar operation for the AI units in our game by creating a list of nodes to traverse to a target node. Hence my use of Astar (the resulting path can be used to create this line). Here is my Algorithm function findShortestPath (startN:node, goalN:node) { var openSet:Array = new Array(); var closedSet:Array = new Array(); var pathFound:Boolean = false; startN.g_score = 0; startN.h_score = distFunction(startN,goalN); startN.f_score = startN.h_score; startN.fromNode = null; openSet.push (startN); var i:int = 0 for(i= 0; i< nodeArray.length; i++) { for(var j:int =0; j<nodeArray[0].length; j++) { if(!nodeArray[i][j].isPathable) { closedSet.push(nodeArray[i][j]); } } } while (openSet.length != 0) { var cNode:node = openSet.shift(); if (cNode == goalN) { resolvePath (cNode); return true; } closedSet.push (cNode); for (i= 0; i < cNode.dirArray.length; i++) { var neighborNode:node = cNode.nodeArray[cNode.dirArray[i]]; if (!(closedSet.indexOf(neighborNode) == -1)) { continue; } neighborNode.fromNode = cNode; var tenativeg_score:Number = cNode.gscore + distFunction(neighborNode.fromNode,neighborNode); if (openSet.indexOf(neighborNode) == -1) { neighborNode.g_score = neighborNode.fromNode.g_score + distFunction(neighborNode,cNode); if (cNode.dirArray[i] >= 4) { neighborNode.g_score -= 4; } neighborNode.h_score=distFunction(neighborNode,goalN); neighborNode.f_score=neighborNode.g_score+neighborNode.h_score; insertIntoPQ (neighborNode, openSet); //trace(" F Score of neighbor: " + neighborNode.f_score + " H score of Neighbor: " + neighborNode.h_score + " G_score or neighbor: " +neighborNode.g_score); } else if (tenativeg_score <= neighborNode.g_score) { neighborNode.fromNode=cNode; neighborNode.g_score=cNode.g_score+distFunction(neighborNode,cNode); if (cNode.dirArray[i]>=4) { neighborNode.g_score-=4; } neighborNode.f_score=neighborNode.g_score+neighborNode.h_score; openSet.splice (openSet.indexOf(neighborNode),1); //trace(" F Score of neighbor: " + neighborNode.f_score + " H score of Neighbor: " + neighborNode.h_score + " G_score or neighbor: " +neighborNode.g_score); insertIntoPQ (neighborNode, openSet); } } } trace ("fail"); return false; } Right now this function creates paths that are often not optimal or wholly inaccurate given the target and this generally happens when I have nodes that are not path able, and I am not quite sure what I am doing wrong right now. If someone could help me correct this I would appreciate it greatly. Some Notes My OpenSet is essentially a Priority Queue, so thats how I sort my nodes by cost. Here is that function function insertIntoPQ (iNode:node, pq:Array) { var inserted:Boolean=true; var iterater:int=0; while (inserted) { if (iterater==pq.length) { pq.push (iNode); inserted=false; } else if (pq[iterater].f_score >= iNode.f_score) { pq.splice (iterater,0,iNode); inserted=false; } ++iterater; } } Thanks!

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  • Using Hidden Markov Model for designing AI mp3 player

    - by Casper Slynge
    Hey guys. Im working on an assignment, where I want to design an AI for a mp3 player. The AI must be trained and designed with the use of a HMM method. The mp3 player shall have the functionality of adapting to its user, by analyzing incoming biological sensor data, and from this data the mp3 player will choose a genre for the next song. Given in the assignment is 14 samples of data: One sample consist of Heart Rate, Respiration, Skin Conductivity, Activity and finally the output genre. Below is the 14 samples of data, just for you to get an impression of what im talking about. Sample HR RSP SC Activity Genre S1 Medium Low High Low Rock S2 High Low Medium High Rock S3 High High Medium Low Classic S4 High Medium Low Medium Classic S5 Medium Medium Low Low Classic S6 Medium Low High High Rock S7 Medium High Medium Low Classic S8 High Medium High Low Rock S9 High High Low Low Classic S10 Medium Medium Medium Low Classic S11 Medium Medium High High Rock S12 Low Medium Medium High Classic S13 Medium High Low Low Classic S14 High Low Medium High Rock My time of work regarding HMM is quite low, so my question to you is if I got the right angle on the assignment. I have three different states for each sensor: Low, Medium, High. Two observations/output symbols: Rock, Classic In my own opinion I see my start probabilities as the weightened factors for either a Low, Medium or High state in the Heart Rate. So the ideal solution for the AI is that it will learn these 14 sets of samples. And when a users sensor input is received, the AI will compare the combination of states for all four sensors, with the already memorized samples. If there exist a matching combination, the AI will choose the genre, and if not it will choose a genre according to the weightened transition probabilities, while simultaniously updating the transition probabilities with the new data. Is this a right approach to take, or am I missing something ? Is there another way to determine the output probability (read about Maximum likelihood estimation by EM, but dont understand the concept)? Best regards, Casper

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  • Is F# a good language for card game AI?

    - by Anthony Brien
    I'm writing a Mahjong Game in C# (the Chinese traditional game, not the solitaire kind). While writing the code for the bot player's AI, I'm wondering if a functional language like F# would be a more suitable language than what I currently use which is C# with a lot of Linq. I don't know much about F# which is why I ask here. To illustrate what I try to solve, here's a quick summary of Mahjong: Mahjong plays a bit like Gin Rummy. You have 13 tiles in your hand, and each turn, you draw a tile and discard another one, trying to improve your hand towards a winning Mahjong hand, which consists or 4 sets and a pair. Sets can be a 3 of a kind (pungs), 4 of a kind (kongs) or a sequence of 3 consecutive tiles (chows). You can also steal another player's discard, if it can complete one of your sets. The code I had to write to detect if the bot can declare 3 consecutive tiles set (chow) is pretty tedious. I have to find all the unique tiles in the hand, and then start checking if there's a sequence of 3 tiles that contain that one in the hand. Detecting if the bot can go Mahjong is even more complicated since it's a combination of detecting if there's 4 sets and a pair in his hand. And that's just a standard Mahjong hand. There's also numerous "special" hands that break those rules but are still a Mahjong hand. For example, "13 unique wonders" consists of 13 specific tiles, "Jade Empire" consists of only tiles colored green, etc. In a perfect world, I'd love to be able to just state the 'rules' of Mahjong, and have the language be able to match a set of 13 tiles against those rules to retrieve which rules it fulfills, for example, checking if it's a Mahjong hand or if it includes a 4 of a kind. Is this something F#'s pattern matching feature can help solve?

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  • How to identify ideas and concepts in a given text

    - by Nick
    I'm working on a project at the moment where it would be really useful to be able to detect when a certain topic/idea is mentioned in a body of text. For instance, if the text contained: Maybe if you tell me a little more about who Mr Balzac is, that would help. It would also be useful if I could have a description of his appearance, or even better a photograph? It'd be great to be able to detect that the person has asked for a photograph of Mr Balzac. I could take a really naïve approach and just look for the word "photo" or "photograph", but this would obviously be no good if they wrote something like: Please, never send me a photo of Mr Balzac. Does anyone know where to start with this? Is it even possible? I've looked into things like nltk, but I've yet to find an example of someone doing something similar and am still not entirely sure what this kind of analysis is called. Any help that can get me off the ground would be great. Thanks!

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  • How to start the web cam by programmatically?

    - by Nitz
    Hello Guys How to start any web cam through programmatically? my main requirement is it should start webcam? and that should be any application - software not a website. we can use any language. So how can start the web cam using programing language? btw... [I am not talking about the power of the webcam][Any web cam means any companies web cam]

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  • Is enemy / bot A.I. part of the model or controller in an MVC game

    - by Iain
    It could be part of the model because it's part of the business logic of the game. It could be part of the controller because it could be seen as simulating player input, which would be considered part of the controller, right? Or would it? What about a normal enemy, like a goomba in Mario? UPDATE: Wow, that's really not the answer I was expecting. As far as I could tell, A.I. is an internal part of the autonomous game system, hence model. I'm still not convinced.

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  • Word characteristics tags

    - by theBlinker
    I want to do a riddle AI chatbot for my AI class. So i figgured the input to the chatbot would be : Something like : "It is blue, and it is up, but it is not the ceiling" Translation : <Object X> <blue> <up> <!ceiling> </Object X> (Answer : sky?) So Input is a set of characteristics (existing \ not existing in the object), output is a matched, most likely object. The domain will be limited to a number of objects, i could input all attributes myself, but i was thinking : How could I programatically build a database of characteristics for a word? Is there such a database available? How could i tag a word, how could i programatically find all it's attributes? I was thinking on crawling wikipedia, or some forum, but i can't see it build any reliable word tag database. Any ideas on how i could achieve such a thing? Any ideas on some literature on the subject? Thank you

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