MIT 6.046J / 18.410J Introduction to Algorithms - Fall 2005

Lecture 15: Dynamic Programming, Longest Common Subsequence

author: Charles E. Leiserson, Department of Brain and Cognitive Sciences, MIT - Massachusetts Institute of Technology

Description

"So, the topic today is dynamic programming. The term programming in the name of this term doesn't refer to computer programming. OK, programming is an old word that means any tabular method for accomplishing something. So, you'll hear about linear programming and dynamic programming. Either of those, even though we now incorporate those algorithms in computer programs, originally computer programming, you were given a datasheet and you put one line per line of code as a tabular method for giving the machine instructions as to what to do..."

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*Slides*
0:00	Introduction to Algorithms - Lecture 15
0:15	Dynamic programming (1)
3:07	Dynamic programming (2)
3:51	Dynamic programming (3)
4:53	Dynamic programming (4)
6:46	Brute-force LCS algorithm (1)
7:46	Brute-force LCS algorithm (2)
11:32	Towards a better algorithm (1)
12:53	Towards a better algorithm (2)
13:37	Towards a better algorithm (3)
16:10	Recursive formulation (1)
18:07	Recursive formulation (2)
19:45	Recursive formulation (3)
24:24	Recursive formulation (4)
29:01	Recursive formulation (5)
30:37	Dynamic-programming hallmark #1 (1)
32:22	Dynamic-programming hallmark #1 (2)
34:11	Recursive algorithm for LCS (1)
36:42	Recursive algorithm for LCS (2)
37:55	Recursion tree (1)
40:32	Recursion tree (2)
41:36	Recursion tree (3)
42:33	Dynamic-programming hallmark #2 (1)
44:33	Dynamic-programming hallmark #2 (2)
45:44	Memoization algorithm (1)
46:27	Memoization algorithm (2)
48:39	Memoization algorithm (3)
54:27	Dynamic-programming algorithm (1)
61:08	Dynamic-programming algorithm (2)
61:55	Dynamic-programming algorithm (3)
64:08	Dynamic-programming algorithm (4)

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