Backtracking
Backtracking is a systematic method for solving constraint satisfaction problems by exploring all possible solutions and backtracking when constraints are violated.
Learning Map
Prerequisites
What's in scope
- Backtracking Fundamentals: Recursive exploration, pruning techniques, state space search, and constraint satisfaction
- Classic Backtracking Problems: N-Queens, Sudoku solver, permutations, combinations, and word search
- Advanced Backtracking: Graph coloring, Hamiltonian cycle, Knight's tour, partition problems, and constraint optimization
How to use this section
- Start with Backtracking Fundamentals to understand core concepts
- Practice Classic Backtracking Problems for essential algorithms
- Explore Advanced Backtracking for complex applications
📄️ Backtracking Fundamentals
Master the core concepts of backtracking algorithms including state space exploration, decision trees, pruning strategies, and constraint satisfaction problems.
📄️ Classic Backtracking Problems
Master fundamental backtracking problems including N-Queens, Sudoku solver, permutations, combinations, and subsets with complete implementations.
📄️ Advanced Backtracking
Master advanced backtracking techniques including word search, palindrome partitioning, constraint propagation, and branch-and-bound optimization.