Dynamic Programmin Patterns - Simple wordings

Here's the breakdown of common DP patterns and their sub problems. I highlighted the keywords that indicate it's likely a dynamic programming problem.

Sequence
This is the most common type of DP problem and a good place to get a feel of dynamic programming. In the recurrence relation,dp[i] normally means max/min/best value for the sequence ending at index i.

House robber - find maximum amount of loot
Coin change - find minimum amount of coins needed to make up an amount

Grid
This is the 2D version of the sequence DP. dp[i][j] means max/min/best value for matrix cell ending at index i, j.

Robot unique paths - number of ways for robot to move from top left to bottom right
Min path sum - find path in a grid with minimum cost
Maximal square - find maximal square of 1s in a grid of 0s and 1s

Dynamic number of subproblems
This is similar to "Sequence DP" except dp[i] depends on a dynamic number of sub problems, e.g. dp[i] = max(d[j]..) for j from 0 to i.

Longest Increasing Subsequence - find the longest increasing sub sequence of an array of numbers
Buy/sell stock with at most K transactions - maximize profit by buying and selling stocks using at most K transaction

Partition
This is a continuation of DFS + memoization problems. These problems are easier to reason and solve with a top-down approach. The key to solve these problems is to draw the state-space tree and then traverse it.

Decode ways - how many ways to decode a string
Word break - partition a word into words in a dictionary
Triangle - find the smallest sum path to traverse a triangle of numbers from top to bottom
Partition to Equal Sum Subsets - partition a set of numbers into two equal-sum subsets

Two Sequences
This type of problem has two sequences in their problem statement. dp[i][j] represents the max/min/best value for the first sequence ending in index i and second sequence ending in index j.

Edit distance - find the minimum distance to edit one string to another
Longest common subsequence - find the longest common subsequence that is common in two sequences

Game theory
This type of problem asks for whether a player can win a decision game. The key to solving game theory problems is to identify winning state, and formulating a winning state as a state that returns a losing state to the opponent

Coins in a line
Divisor game
Stone game

Range
dp[i][j] here means the best way to get optimal results using elements in range [i..j].
Bursting balloons

Read more about intro to DP https://algo.monster/problems/dynamic_programming_intro and other patterns summarized here https://algo.monster/problems/stats