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Search found 157 results on 7 pages for 'genetic'.

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• How to optimize neural network by using genetic algorithm?

  - by Billy Coen

  I'm quite new with this topic so any help would be great. What i need is to optimize a neural network in MATLAB by using GA. My network has [2x98] input and [1x98] target, i've tried consulting matlab help but im still kind of clueless about what to do :( so, any help would be appreciated. Thanks in advance. edit: i guess i didn't say what is there to be optimized as Dan said in the 1st answer. I guess most important thing is number of hidden neurons. And maybe number of hidden layers and training parameters like number of epochs or so. Sorry for not providing enough info, i'm still learning about this.

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• automatic test data generate using genetic algo in matlab.

  - by shalini

  hi, i m doing my project in software testing. gnetic algorithm is the technique i want to use to generate automatic test data\test cases in matlab. please help me in doing my project successfully. thanks.

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• Rather than sending in numbers, having code passed to an individual in genetic programming? ECJ

  - by sieve411

  I'm using ECJ with Java. I have an army of individuals who I all want to have the same brain. Basically, I'd like to evolve the brains using GP. I want things like "if-on-enemy-territory" and "if-sense-target" for if statements and "go-home" or "move-randomly" or "shoot" for terminals. However, these statements need to be full executable Java code. How can I do this with ECJ?

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• How do you avoid an invalid search space in a genetic algorithm?

  - by Dave

  I am developing a GA for a school project and I've noticed that upon evaluating my functions for fitness, an individual is equivalent to its inverse. For example, the set (1, 1, -1, 1) is equivalent to (-1, -1, 1, -1). To shrink my search space and reach a solution more efficiently, how can I avoid my crossovers from searching in this second half of the search space?

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• Code bacteria: evolving mathematical behavior

  - by Stefano Borini

  It would not be my intention to put a link on my blog, but I don't have any other method to clarify what I really mean. The article is quite long, and it's in three parts (1,2,3), but if you are curious, it's worth the reading. A long time ago (5 years, at least) I programmed a python program which generated "mathematical bacteria". These bacteria are python objects with a simple opcode-based genetic code. You can feed them with a number and they return a number, according to the execution of their code. I generate their genetic codes at random, and apply an environmental selection to those objects producing a result similar to a predefined expected value. Then I let them duplicate, introduce mutations, and evolve them. The result is quite interesting, as their genetic code basically learns how to solve simple equations, even for values different for the training dataset. Now, this thing is just a toy. I had time to waste and I wanted to satisfy my curiosity. however, I assume that something, in terms of research, has been made... I am reinventing the wheel here, I hope. Are you aware of more serious attempts at creating in-silico bacteria like the one I programmed? Please note that this is not really "genetic algorithms". Genetic algorithms is when you use evolution/selection to improve a vector of parameters against a given scoring function. This is kind of different. I optimize the code, not the parameters, against a given scoring function.

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• deciphering columnar transposition cipher

  - by Arfan M

  I am looking for an idea on how to decipher a columnar transposition cipher without knowing the key or the length of the key. When I take the cipher text as input to my algorithm I will guess the length of the key to be the factors of the length of the cipher text. I will take the first factor suppose the length was 20 letters so I will take 2*10 (2 rows and 10 columns). Now I want to arrange the cipher text in the columns and read it row wise to see if there is any word forming and match it with a dictionary if it is something sensible. If it matches the dictionary then it means it is in correct order or else I want to know how to make other combinations of the columns and read the string again row wise. Please suggest another approach that is more efficient.

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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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• MATLAB: Best fitness vs mean fitness, initial range

  - by Sa Ta

  Based on the example of Rastrigin's function. At the plot function, if I chose 'best fitness', on the same graph 'mean fitness' will also be plotted. I understand well about 'best fitness' whereby it plots the best function value in each generation versus iteration number. It will reach value zero after some times. I don't understand about 'mean fitness'in the graph plotted. What do those 'mean fitness' values mean? How does the 'mean fitness' graph help to understand Rastrigin's function? What are the meaning of the term initial population, initial score and initial range? I wish to have a better understanding of these terms. The default value for initial range is [0,1]. Does it mean that 0 is the lower bound (lb) and 1 is the upper bound (ub)? Do these values interfere with the lb and ub values I set in the constraints? I try to better understand about lb and ub. If my lb is 0 and ub is 5, does it mean that my final point values will be within 0 and 5? If I know the lb and ub for my problem is between 0 and 5, do I just set the initial range as [0,5] at all times and may I assume that this is the best option for initial range, and I need not try it with any other values?

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• Given two sets of DNA, what does it take to computationally "grow" that person from a fertilised egg and see what they become? [closed]

  - by Nicholas Hill

  My question is essentially entirely in the title, but let me add some points to prevent some "why on earth would you want to do that" sort of answers: This is more of a mind experiment than an attempt to implement real software. For fun. Don't worry about computational speed or the number of available memory bytes. Computers get faster and better all of the time. Imagine we have two data files: Mother.dna and Father.dna. What else would be required? (Bonus point for someone who tells me approx how many GB each file will be, and if the size of the files are exactly the same number of bytes for everyone alive on Earth!) There would ideally need to be a way to see what the egg becomes as it becomes a human adult. If you fancy, feel free to outline the design. I am initially thinking that there'd need to be some sort of volumetric voxel-based 3D environment for simulation purposes.

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• How to guard against dividing by zero when doing symbolic regression? ECJ

  - by Charlie

  I'm writing a genetic program to perform symbolic regression on a formula. I'm using ECJ. See tutorial 4 for an example of what this is and the base that I started off of. The problem comes when implementing division as a function to your genetic program. How do you guard against dividing by zero?

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• Genetic/Evolutionary algorithms and local minima/maxima problem

  - by el.gringogrande

  I have run across several posts and articles that suggests using things like simulated annealing to avoid the local minima/maxima problem. I don't understand why this would be necessary if you started out with a sufficiently large random population. Is it just another check to insure that the initial population was, in fact, sufficiently large and random? Or are those techniques just an alternative to producing a "good" initial population?

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• how to tackle this combinatorial algorithm problem

  - by Andrew Bullock

  I have N people who must each take T exams. Each exam takes "some" time, e.g. 30 min (no such thing as finishing early). Exams must be performed in front of an examiner. I need to schedule each person to take each exam in front of an examiner within an overall time period, using the minimum number of examiners for the minimum amount of time (i.e. no examiners idle) There are the following restrictions: No person can be in 2 places at once each person must take each exam once noone should be examined by the same examiner twice I realise that an optimal solution is probably NP-Complete, and that I'm probably best off using a genetic algorithm to obtain a best estimate (similar to this? http://stackoverflow.com/questions/184195/seating-plan-software-recommendations-does-such-a-beast-even-exist). I'm comfortable with how genetic algorithms work, what i'm struggling with is how to model the problem programatically such that i CAN manipulate the parameters genetically.. If each exam took the same amount of time, then i'd divide the time period up into these lengths, and simply create a matrix of time slots vs examiners and drop the candidates in. However because the times of each test are not necessarily the same, i'm a bit lost on how to approach this. currently im doing this: make a list of all "tests" which need to take place, between every candidate and exam start with as many examiners as there are tests repeatedly loop over all examiners, for each one: find an unscheduled test which is eligible for the examiner (based on the restrictions) continue until all tests that can be scheduled, are if there are any unscheduled tests, increment the number of examiners and start again. i'm looking for better suggestions on how to approach this, as it feels rather crude currently.

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• Suggested GA operators for a TSP problem?

  - by Mark

  I'm building a genetic algorithm to tackle the traveling salesman problem. Unfortunately, I hit peaks that can sustain for over a thousand generations before mutating out of them and getting better results. What crossover and mutation operators generally do well in this case?

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• Artificial Inteligence library in python

  - by João Portela

  I was wondering if there are any python AI libraries similar to aima-python but for a more recent version of python... and how they are in comparison to aima-python. I was particularly interested in search algorithms such as hill-climbing, simulated annealing, tabu search and genetic algorithms. edit: made the question more clear.

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• Balancing heuristics (for timetable problem)

  - by genesiss

  I'm writing a genetic algorithm for generating timetables. At the moment I'm using these two heuristics: Number of holes between lectures in one day (related) (less holes - bigger score) Each hour has some value, so for each timetable I sum values for hours when lectures are on. (lectures at more appropriate hours - bigger score) I want to balance these two heuristics, so the algorithm wouldn't favor neither one. What would be the best way to achieve this?

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• Travelling Salesman Problem Constraint Representation

  - by alex25

  Hey! I read a couple of articles and sample code about how to solve TSP with Genetic Algorithms and Ant Colony Optimization etc. But everything I found didn't include time (window) constraints, eg. "I have to be at customer x before 12am)" and assumed symmetry. Can somebody point me into the direction of some sample code or articles that explain how I can add constraints to TSP and how I can represent those in code. Thanks!

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• How to get a random node from a tree?

  - by ooboo

  It looks easy, but I found the implementation tricky. I need that for a simple genetic programming problem I'm trying to implement. The function should, given a node, return the node itself or any of its children such that the probability of choosing a node is normally distributed relative to its depth (so the function should return mostly middle nodes, but sometimes the root itself or the lowest ones - but that's not really necessary if that makes it significantly more complex, if all any node is chosen with equal probability, that's good enough). Thanks

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• Can you please provide some topic ideas related to AI to be used in a project?

  - by mouthpiec

  I need topic ideas related to AI on which I will base my thesis. I am mostly interested in Genetic Algorithm and Neural Networks techniques. I already got the some ideas, but non of them seems to hit me! Any help will be really appreciated!! :)

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• Using GA in GUI

  - by AlexT

  Sorry if this isn't clear as I'm writing this on a mobile device and I'm trying to make it quick. I've written a basic Genetic Algorithm with a binary encoding (genes) that builds a fitness value and evolves through several iterations using tournament selection, mutation and crossover. As a basic command-line example it seems to work. The problem I've got is with applying a genetic algorithm within a GUI as I am writing a maze-solving program that uses the GA to find a method through a maze. How do I turn my random binary encoded genes and fitness function (add all the binary values together) into a method to control a bot around a maze? I have built a basic GUI in Java consisting of a maze of labels (like a grid) with the available routes being in blue and the walls being in black. To reiterate my GA performs well and contains what any typical GA would (fitness method, get and set population, selection, crossover, etc) but now I need to plug it into a GUI to get my maze running. What needs to go where in order to get a bot that can move in different directions depending on what the GA says? Rough pseudocode would be great if possible As requested, an Individual is built using a separate class (Indiv), with all the main work being done in a Pop class. When a new individual is instantiated an array of ints represent the genes of said individual, with the genes being picked at random from a number between 0 and 1. The fitness function merely adds together the value of these genes and in the Pop class handles selection, mutation and crossover of two selected individuals. There's not much else to it, the command line program just shows evolution over n generations with the total fitness improving over each iteration. EDIT: It's starting to make a bit more sense now, although there are a few things that are bugging me... As Adamski has suggested I want to create an "Agent" with the options shown below. The problem I have is where the random bit string comes into play here. The agent knows where the walls are and has it laid out in a 4 bit string (i.e. 0111), but how does this affect the random 32 bit string? (i.e. 10001011011001001010011011010101) If I have the following maze (x is the start place, 2 is the goal, 1 is the wall): x 1 1 1 1 0 0 1 0 0 1 0 0 0 2 If I turn left I'm facing the wrong way and the agent will move completely off the maze if it moves forward. I assume that the first generation of the string will be completely random and it will evolve as the fitness grows but I don't get how the string will work within a maze. So, to get this straight... The fitness is the result of when the agent is able to move and is by a wall. The genes are a string of 32 bits, split into 16 sets of 2 bits to show the available actions and for the robot to move the two bits need to be passed with four bits from the agent showings its position near the walls. If the move is to go past a wall the move isn't made and it is deemed invalid and if the move is made and if a new wall is found then the fitness goes up. Is that right?

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• Can I use a genetic algorithm for balancing character builds?

  - by Renan Malke Stigliani

  I'm starting to build a online PVP (duel like, one-on-one) game, where there is leveling, skill points, special attacks and all the common stuff. Since I have never done anything like this, I'm still thinking about the math behind the levels/skills/specials balance. So I thought a good way of testing the best builds/combos, would be to implement a Genetic Algorithm. It'd be like this: Generate a big group of random characters Make them fight, level them up accordingly to their victories(more XP)/losses(less XP) Mate the winners, crossing their builds, to try and make even better characters Add some more random chars, emulating new players Repeat the process for some time, or util I find some chars who can beat everyone's butt I could then play with the math and try to find better balances to make sure that the top x% of chars would be a mix of various build types. So, is it a good idea, or is there some other, easier method to do the balancing?

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• How can I extract similarities/patterns from a collection of binary strings?

  - by JohnIdol

  I have a collection of binary strings of given size encoding effective solutions to a given problem. By looking at them, I can spot obvious similarities and intuitively see patterns of symmetry and periodicity. Are there mathematical/algorithmic tools I can "feed" this set of strings to and get results that might give me an idea of what this set of strings have in common? By doing so I would be able to impose a structure (or at least favor some features over others) on candidate solutions in order to greatly reduce the search space, maximizing chances to find optimal solutions for my problem (I am using genetic algorithms as the search tool - but this is not pivotal to the question). Any pointers/approaches appreciated.

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• Setting up java configurations in eclipse..Param files

  - by Charlie

  I'm going to be using ECJ for doing genetic programming and I haven't touched java in years. I'm working on setting up the eclipse environment and I'm catching a few snags. The ECJ source has several packages, and several sample programs come along with it. I ran one sample program (called tutorial1) by going to the run configurations and adding -file pathToParamsFile to the program arguments. This made it point to the params file of that tutorial and run that sample. In a new example I am testing (from the package gui) there are TWO params files. I tried pointing to just one param file and a program ran in the console, but there was supposed to be a GUI which did not load. I'm not sure what I'm doing wrong. Any help would be greaaatly appreciated.

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• How to create a container that holds different types of function pointers in C++?

  - by Alex

  I'm doing a linear genetic programming project, where programs are bred and evolved by means of natural evolution mechanisms. Their "DNA" is basically a container (I've used arrays and vectors successfully) which contain function pointers to a set of functions available. Now, for simple problems, such as mathematical problems, I could use one type-defined function pointer which could point to functions that all return a double and all take as parameters two doubles. Unfortunately this is not very practical. I need to be able to have a container which can have different sorts of function pointers, say a function pointer to a function which takes no arguments, or a function which takes one argument, or a function which returns something, etc (you get the idea)... Is there any way to do this using any kind of container ? Could I do that using a container which contains polymorphic classes, which in their turn have various kinds of function pointers? I hope someone can direct me towards a solution because redesigning everything I've done so far is going to be painful.

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• Setting up java configurations in eclipse. multiple .param files

  - by Charlie

  I'm going to be using ECJ for doing genetic programming and I haven't touched java in years. I'm working on setting up the eclipse environment and I'm catching a few snags. The ECJ source has several packages, and several sample programs come along with it. I ran one sample program (called tutorial1) by going to the run configurations and adding -file pathToParamsFile to the program arguments. This made it point to the params file of that tutorial and run that sample. In a new example I am testing (from the package gui) there are TWO params files. I tried pointing to just one param file and a program ran in the console, but there was supposed to be a GUI which did not load. I'm not sure what I'm doing wrong. Any help would be greaaatly appreciated.

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• Genetics algorithms theoretical question

  - by mandelart

  Hi All! I'm currently reading "Artificial Intelligence: A Modern Approach" (Russell+Norvig) and "Machine Learning" (Mitchell) - and trying to learn basics of AINN. In order to understand few basic things I have two 'greenhorn' questions: Q1: In a genetic algorithm given the two parents A and B with the chromosomes 001110 and 101101, respectively, which of the following offspring could have resulted from a one-point crossover? a: 001101 b: 001110 Q2: Which of the above offspring could have resulted from a two-point crossover? and why? Please advise.

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