Constraint Satisfaction Problems Overview/Description Target Audience Prerequisites Expected Duration Lesson Objectives Course Number Expertise Level Overview/Description
Search algorithms provide solutions for many problems, but they aren't always the optimal solution. This course will show you how constraint satisfaction algorithms are better than search algorithms in some cases, and how to use them.
Target Audience
Anyone interested in artificial intelligence and how it can be used to solve many problems
Prerequisites
None
Expected Duration (hours)
0.5
Lesson Objectives Constraint Satisfaction Problems
start the course
define constraint satisfaction problems and describe how they are different from search problems
list some examples of problems that are better for constraint satisfaction algorithms than search algorithms
describe how to use a backtracking search to solve a constraint satisfaction problem
describe how to order variables when performing a backtracking search
describe arc consistency and other types of constraint consistency in a constraint satisfaction problem
describe how to use arc consistency to solve a constraint satisfaction problem with constraint propagation
describe how to use the backjumping and forward checking inference method in a backtracking search
describe how local search algorithms can be used to solve constraint satisfaction problems
describe how to represent a Sudoku puzzle and how to solve it as a constraint satisfaction problem
build a full high-level representation and solution for a constraint satisfaction problem
Course Number: sd_exai_a03_it_enus
Expertise Level
Intermediate