Artificial intelligence
$30-250 USD
Płatność przy odbiorze
Polyominoes puzzle is one of the most famous single player games that can be played in so many forms. One of these forms consists of an n × m board that should be covered by some of a given collection of tiles in some certain order.
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This project aims to build an efficient solver to solve a simpler version of Polyomino, where each one of its tiles contain some numbers that matches the main board position numbers. The player should find the best collection of tiles that covers all the board (if possible) without any overlapping.
Problem Description
The input:
Given a set X and a collection S of subsets of X.
The goal…
Find a sub-collection S* of S that satisfies the two conditions:
* The intersection of any two distinct subsets in S* is empty (no overlapping) .
* The union of the subsets in S* is X.
For example :
Let set X = {1, 2, 3, 4, 5}, and S ={A, B, C, D, E} be a collection of subsets:
* A={1, 5}
* B={1, 3, 4}
* C={3, 4}
* D={2, 4}
* E={3}
The sub-collection S* = {A, D, E} is exact covering solution for X.
Requirements
1. Incremental Formulation
Give an incremental formulation for the exact cover problem, providing a precise definition of the following components:
* Initial state.
* Successor function.
* Goal test.
* Solution cost.
2. Optimization Problem Formulation
Formulate the problem as an optimization problem, providing a precise definition of the
following components:
* Solution representation, i.e. how a candidate solution (sequence) is represented.
* The objective function. Given a candidate solution following the representation you
suggested, the objective function should return a numerical value to measure the
quality of the solution.
3. Illustration
Use the previous example to illustrate the components of questions 1 & 2.
4. Analysis
Analyze the size of the state (i.e. search) space in terms of N where N is the number of
subsets.
5. Neighborhood Function
Based on the solution representation given in question 2, suggest at least one (or may be multiple) effective neighborhood function of a local search algorithm. Remember that a neighborhood function maps a candidate solution S to a set of other solutions by applying small (i.e. local) changes to S.
6. Genetic Algorithms
Based on the solution representation given in question 2, suggest effective crossover and mutation operators of a Genetic Algorithm.
Numer ID Projektu: #13816449
O projekcie
15 freelancerów złożyło ofertę za $164 w tym projekcie
Hello I am Java and Algorithm expert and interested in this project. I have reviewed the details and confident to handle it perfectly. I have a lot of experience in helping in students with assignments, so I wi Więcej
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I am an IITK graduate and I have 9 years of experience in software development. I have 100% completion rate and I have finished all the projects with the highest level of customer satisfaction. I usually finish project Więcej
Hi! I would like to help you with this project, so, you can contact me over chat if you want to. I know genetic algorithms really well and can answer those questions that you are required to answer. :) Regards and all Więcej
Hi Dear I have a lot experience in Data Analysis, Statistic,Business Intelligence,Data Mining, Machine Learning . I am Data Analysis Certified from spss Analytics. I have done all kind of Data Analysis like One way A Więcej
I have a detailed experience in AI and in mathematical optimization. In addition, I am well versed in probabilistic modelling. I should be able to design this solver for you.