Python constraint backtracking solver

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Python constraint backtracking solver

A solver for the n Queens problem, using the backtracking algorithm. Project to learn and understand backtracking algorithms with the goal to solve a crossword puzzle. A simple android app of genetic algorithm and backtracking implementation to solve 8-queen problem. Implementation of Peter Norvig's sudoku solving and backtracking algorithms in java.

Using recursive backtracking to implement Wang Tiles to "randomly" create an image from smaller images that are similar. A school project for Artificial Intelligence: Search for room scheduling. Solution of various problems that can be only solved with backtracking.

This is a Sudoku solving program repository. It contains a set of programs that can successfully solve a Sudoku provided that the solution exists. Each program implements a different algorithm with different time complexities.

A input file is also included to test for the potential inputs. C application which uses a backtracking algorithm to create team combinations of player objects sorted by their total "team skill. Project focuses on optimised implementation of Backtracking and Forward Checking algorithms in order to find all solutions of the N Queens problem. This program solves sudokus with all possible solutions using backtraking.

A text-based sudoku solver that utilizes a recursive backtracking algorithm to find a solution for 9x9 puzzles. This is a java sudoku solver. Add a description, image, and links to the backtracking-algorithm topic page so that developers can more easily learn about it. Curate this topic. To associate your repository with the backtracking-algorithm topic, visit your repo's landing page and select "manage topics. Learn more. We use optional third-party analytics cookies to understand how you use GitHub.

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Star 1.Backtracking is an approach to solving constraint-satisfaction problems without trying all possibilities. These problems are interesting because there are so many candidate solutionsthe vast majority of which do not satisfy the given constraints. Not really, because:.

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Would you try to build up a solution, digit-by-digit? When nothing works in a slot, you have to backtrack. For each example, Notice the formulation of the problem into slots and values. Watch carefully for the occurences of backtracking.

python constraint backtracking solver

Eight-Queens For each column For each country, try the colors red, green, orange, yellow in turn, so that no two adjacent countries have the same color. For each slot For each non-fixed square, try each of the values Yes, there are better ways, but this will do for now.

At each square, try going up, then left, then right, then down. Whenever the new square has not been visited, move there. When you have to backtrack, mark the square as fully explored.

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Each root-to-leaf-path is a candidate solution. Here are the candidates for the no-equal-substring problem, using the digits 0, 1, and 2, of length I only had room to show 4 levels 81 possible solutions, nodes total ; showing even 10 levels would require 59, leaf nodes 88, total nodesand 50 levels would be, well, you get the idea. To solve a constraint problem we search for a solution. A brute-force algorithm searchs the whole tree, but with backtracking, we get to throw away massive parts of the tree when we discover a partial solution cannot be extended to a complete solution.

So after realizing the second value cannot be a zero, you can avoid considering i. We built up a search tree with only 21 nodes, as opposed to 88, Each of the problems above are in the some sense the same problem. So we can write a backtracking engine that is parameterized by the type of slots, the values for each slot, and a function that determines whether the current partial solution is safe.

Is this the best way? Perhaps we should ask this on Codereview dot StackExchange dot com. Seriously, why not? The solutions above used recursion to implement backtracking.The first thing we have to understand while dealing with constraint programming is that the way of thinking is very different from our usual way of thinking when we sit down to write code.

Constraint programming is an example of the declarative programming paradigm, as opposed to the usual imperative paradigm that we use most of the time. A paradigm means "an example" or "a pattern" of something. A programming paradigm is often described as a "way of thinking" or "way of programming". The most common examples including Procedural programming e. CObject-Oriented programming e. Java and Functional Programming e. Most programming paradigms can be classified as a member of either the imperative or declarative paradigm group.

In this article we'll be working with a module called python-constraint Note: there's a module called "constraint" for Python, that is not what we wantwhich aims to bring the constraint programming idea to Python. This is the generalized skeleton of programs written using this module Note: we use import constraint and not import python-constraint.

As previously mentioned, constraint programming is a form of declarative programming. The order of statements doesn't matter, as long as everything is there in the end. It's usually used to solve problems like this:.

If we look at this sentence, we can see several conditions let's call them constraints that x and y have to meet. For example, x is "constrained" to the values 1,2,3y has to be less than 10 and their sum has to be greater than or equal to 5. This is done in a few lines of code and in a few minutes using constraint programming.

Looking at the problem above you probably thought "So what?

python constraint backtracking solver

I can do this with 2 for loops and half a cup of coffee in Python in less than 10 minutes". You're absolutely right, though through this example we can get an idea of what constraint programming looks like:. Let's walk through this program step by step.By using our site, you acknowledge that you have read and understand our Cookie PolicyPrivacy Policyand our Terms of Service.

Stack Overflow for Teams is a private, secure spot for you and your coworkers to find and share information. I want to write a code in python to solve a sudoku puzzle. Do you guys have any idea about a good algorithm for this purpose. I read somewhere in net about a algorithm which solves it by filling the whole box with all possible numbers, then inserts known values into the corresponding boxes.

From the row and coloumn of known values the known value is removed. If you guys know any better algorithm than this please help me to write one. Also I am confused that how i should read the known values from the user. It is really hard to enter the values one by one through console. Any easy way for this other than using gui?

Here is my sudoku solver in python. It uses simple backtracking algorithm to solve the puzzle. For simplicity no input validations or fancy output is done. It's the bare minimum code which solves the problem. It takes 9X9 grid partially filled with numbers. A cell with value 0 indicates that it is not filled. The above one is very basic backtracking algorithm which is explained at many places.

But the most interesting and natural of the sudoku solving strategies I came across is this one from here. I also wrote a Sudoku solver in Python. It is a backtracking algorithm too, but I wanted to share my implementation as well. Backtracking can be fast enough given that it is moving within the constraints and is choosing cells wisely.

You might also want to check out my answer in this thread about optimizing the algorithm. But here I will focus on the algorithm and code itself. The gist of the algorithm is to start iterating the grid and making decisions what to do - populate a cell, or try another digit for the same cell, or blank out a cell and move back to the previous cell, etc.

It's important to note that there is no deterministic way to know how many steps or iterations you will need to solve the puzzle.

Therefore, you really have two options - to use a while loop or to use recursion. Both of them can continue iterating until a solution is found or until a lack of solution is proven.

The advantage of the recursion is that it is capable of branching out and generally supports more complex logics and algorithms, but the disadvantage is that it is more difficult to implement and often tricky to debug.By using our site, you acknowledge that you have read and understand our Cookie PolicyPrivacy Policyand our Terms of Service. Stack Overflow for Teams is a private, secure spot for you and your coworkers to find and share information. Could someone explain to me, or refer me to any web page where it explains the meaning of the last 3 lines of this code?

Moreover, how could I use the AllDifferentConstraint constraint to make the below code shorter? Learn more. Asked 5 years, 5 months ago. Active 5 years, 5 months ago. Viewed times. Bhargav if the OP doesn't understand the code, there's really no point reviewing it for them.

Bhargav Explanations of code are off-topic for Code Review. Please read their help center before making recommendations. Furthermore, if you feel this question is not a good fit for Stack Overflow, consider explaining why and make recommendations that could make this question a better fit.

Without knowing the definition of the Problem class or what module it's defined in, it's not possible to explain what that code snippet is doing. I'm guessing that it's using python-constraint. So you need to read their docs, and the relevant literature; IMHO, this question in its current form is not suitable for Stackoverflow. That lambda function describes the constraint that prevents queens from attacking each other.

Do you see how it works? It looks like I guessed the correct module, since you've accepted Poke's answer. Active Oldest Votes.

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I'm not sure what is the value of row1 and row2 because it's not defined above. Notice, I'm new to Python.

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Apparently, addConstraint expects a function that has two parameters which we call row1 and row2 and a 2-tuple of columns. I appreciate it.

According to my understanding, row1 and row2 will have same value of col1 and col2, because it passed from col1 an dcol No, constraintFunction is called with those two columns, but constraintFunction then returns a different function— innerFunction —which has row1 and row2 as parameters.

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python constraint backtracking solver

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