• Online, Self-Paced
Course Description

Many problems faced by intelligent agents can be solved using searching methods. This course will provide you with a definition for search problems and useful methods to solve these problems.

Learning Objectives

Introducing Search Problems

  • start the course
  • define search problems and how these can be used by AI agents
  • list some problems that are ideal for searching algorithms
  • define how to represent search problems


Brute Force Searching

  • describe the breadth-first search algorithm
  • describe the depth-first search algorithm
  • describe depth-limited search and the iterative deepening search algorithms


Informed Searching

  • describe the greedy approach for best-first informed searching
  • define heuristics and their various properties
  • describe how to create a good heuristic function for a given search problem
  • describe the A* search algorithm


Local Searching

  • describe local searching and the hill-climbing search algorithm
  • describe the simulated annealing search algorithm and how it improves on hill-climbing search


Practice: Identifying Search Problems

  • describe the three environmental characteristics of search problems, state the function for a consistent heuristic, and state the function for an A* search


Framework Connections

The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):

Specialty Areas

  • Software Development
  • Technology R&D