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.

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.

    Learning Practice

  • 3.1

    Introduction To Problem Solving In Ai

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

    Learning Practice

  • 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.

    Learning Practice

  • 3.2

    Uninformed Search Strategies

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

    Learning Practice

  • 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.

    Learning Practice

  • 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.

    Learning Practice

  • 3.3

    Informed Search Strategies

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

    Learning Practice

  • 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.

    Learning Practice

  • 3.3.2

    A Search*

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

    Learning Practice

  • 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.

    Learning Practice

  • 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.

    Learning Practice

  • 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.

    Learning Practice

References

Chapter 3_ Search Algorithms and Problem Solving.pdf

Class Notes

Memorization

What we have learnt

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

Final Test

Revision Tests

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