46. Introduction to Algorithmic Paradigms
Algorithmic paradigms are general strategies or approaches used to design a computer algorithm to solve a particular class of problems. Understanding these strategies is key to solving complex problems.
Key Paradigms We Will Cover
- Divide and Conquer: Breaking a problem into independent subproblems, solving them, and combining the results (e.g., Merge Sort, Quick Sort).
- Greedy Algorithms: Making the locally optimal choice at each step, hoping to find a globally optimal solution (e.g., Dijkstra's, Kruskal's).
- Dynamic Programming (DP): Solving overlapping subproblems by storing the results of intermediate calculations to avoid recomputing them (e.g., Fibonacci sequence optimization, Knapsack problem).
- Backtracking: A refinement of brute-force search that attempts to find a solution by building it up piece by piece, abandoning partial solutions when they violate constraints.