AI Course Fundamental | Search Algorithms and Problem Solving by Diljeet Singh | Learn Smarter
K12 Students

Academics

AI-Powered learning for Grades 8–12, aligned with major Indian and international curricula.

Academics
Professionals

Professional Courses

Industry-relevant training in Business, Technology, and Design to help professionals and graduates upskill for real-world careers.

Professional Courses
Games

Interactive Games

Fun, engaging games to boost memory, math fluency, typing speed, and English skills—perfect for learners of all ages.

games
Search Algorithms and Problem Solving

Search algorithms are vital in artificial intelligence for solving problems by navigating a space of possible solutions. Uninformed strategies, like Breadth-First Search and Depth-First Search, operate without domain-specific knowledge, while informed strategies, such as A* and Greedy Best-First Search, utilize heuristics for efficient problem solving. The chapter emphasizes the need for effective heuristics and optimization techniques to tackle real-world problems effectively.

Enroll to start learning

You’ve not yet enrolled in this course. Please enroll for free to listen to audio lessons, classroom podcasts and take practice test.

Sections

  • 3

    Search Algorithms And Problem Solving

    This section examines search algorithms as a critical component of problem-solving in AI, focusing on both uninformed and informed strategies.

  • 3.1

    Introduction To Problem Solving In Ai

    Problem solving in AI involves utilizing search algorithms to find paths to solutions.

  • 3.1.1

    Problem-Solving Agent

    A problem-solving agent in AI utilizes search strategies to find paths from initial to goal states within a solution space.

  • 3.2

    Uninformed Search Strategies

    Uninformed search strategies explore the solution space in a blind manner without specific knowledge about the domain.

  • 3.2.1

    Breadth-First Search (Bfs)

    BFS is an uninformed search strategy that explores all nodes at the present depth before moving on to nodes at the next depth level.

  • 3.2.2

    Depth-First Search (Dfs)

    Depth-First Search (DFS) is a search algorithm that explores as far as possible along each branch before backtracking, utilizing a stack data structure.

  • 3.3

    Informed Search Strategies

    Informed search strategies utilize heuristic knowledge to navigate the search space efficiently, contrasting with uninformed methods.

  • 3.3.1

    Greedy Best-First Search

    Greedy Best-First Search is an informed search algorithm that employs a heuristic to guide its search towards the goal efficiently.

  • 3.3.2

    A Search*

    A* search algorithm combines costs and heuristics for efficient problem-solving, ensuring completeness and optimality with admissible heuristics.

  • 3.4

    Heuristics And Optimization

    This section explores heuristics and optimization techniques in search algorithms, providing insights into how heuristics can guide problem-solving more efficiently.

  • 3.4.1

    What Is A Heuristic?

    A heuristic is a practical rule of thumb used to estimate the cost of reaching a goal from a given state, allowing search algorithms to prioritize certain paths.

  • 3.4.2

    Optimization In Search

    This section explores optimization techniques in search algorithms, focusing on methods used to find the best possible solutions in real-world problems.

Class Notes

Memorization

What we have learnt

  • A problem-solving agent uti...
  • Uninformed search strategie...
  • Effective heuristics enhanc...

Final Test

Revision Tests