There are 2 repositories under constraint-satisfaction topic.
A Robust Inverse Kinematics Library
Successive Convexification with Continuous-Time Constraint Satisfaction
(WIP) Optimizing bin packing constraint solver for Elixir
Solve Sudoku with Python using the CSF approach
A rule checker library for Java. Checks sets of rules for completeness, overlap, and constraint satisfaction.
Proof of concept
Experiments in building a constraint workbench.
Bio-ModelChecker: Using Bounded Constraint Satisfaction to Seamlessly Integrate Observed Behavior with Prior Knowledge of Biological Networks
Search, Knowledge, Uncertainty, Optimization, Learning, Neural Networks and Language.
A Kakuro puzzle solver using backtracking search with optional Least Constraining Value (LCV) heuristic. Supports multiple difficulty levels with step-by-step terminal visualization.
Encoding Vesicle Traffic System in Z3 and CBMC
Efficient propagating sudoku solver
Professional test scheduling system with dual modes: time-based and sequence-based
Generates two clash-free class schedules using a genetic algorithm with random selection, crossover, and mutation. Designed for 3 teachers over 3 days and 3 periods.
Sudoku Solver Python-based using recursion and backtracking to instantly solve Sudoku puzzles with ease.
Algorithms on the Box Wrapping Problem
an artificial intelligence project to solve the N-queen constraint satisfaction problem
Sudoku Solver is a repository dedicated to the development and benchmark of famous and novel approaches to solve Sudoku puzzles up to 17 clues
Constraints solving (sequencing, priority) as a command line tool. Type your constraints in simple plain text. Generation of Graphviz compatible documents that can be rendered as a diagram!
Interactive logic puzzle solver using Prolog and WebAssembly with step-by-step reasoning visualization
This is a puzzle solver created from scratch by myself, with the purpose of practice and fun. If you are looking for a solver for the puzzle below or interested in how the solver was formulated, this page is for you! Disclaimer: I did not create the puzzle.
Graph-based university course scheduling system using Neo4j with constraint satisfaction (lecturer availability, room capacity, and time conflicts).
🎓 AI-Powered Timetable Generator using CSP, Graph Theory & Machine Learning | Flask Web App with Advanced Algorithms
Prolog owl puzzle constraint satisfaction - CST233 Programming Languages
Java-based Sudoku solver that uses graph-based techniques to find solutions efficiently.
Final compliant solution: Dijkstra from scratch, backtracking CSP, transposition-invariant pattern analysis; no dict/set; interactive CLI