Genetic Algorithm Chapter 7: GA in Robotics
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Questions and Answers

What is the final solution path obtained from the given iterations?

  • S----> G----->F
  • S----> B----->F
  • S----> B----->F----> G (correct)
  • S----> F----->B
  • What is the time complexity of Greedy best-first search in the worst case?

  • O(log n)
  • O(bm) (correct)
  • O(n^2)
  • O(b^n)
  • What is the space complexity of Greedy best-first search in the worst case?

  • O(bm) (correct)
  • O(b^n)
  • O(log n)
  • O(n^2)
  • Is Greedy best-first search complete?

    <p>No</p> Signup and view all the answers

    Is Greedy best-first search optimal?

    <p>No</p> Signup and view all the answers

    What is A* search algorithm?

    <p>A type of informed search</p> Signup and view all the answers

    What is the evaluation function used in A* search algorithm?

    <p>g(n) + h(n)</p> Signup and view all the answers

    What happens when the goal node is found in A* search algorithm?

    <p>The algorithm stops and returns success</p> Signup and view all the answers

    What is the purpose of the OPEN list in A* search algorithm?

    <p>To store the nodes that are yet to be expanded</p> Signup and view all the answers

    What happens to a node when it is expanded in A* search algorithm?

    <p>It is added to the CLOSED list</p> Signup and view all the answers

    Study Notes

    The use of GA in the field of robotics

    • Genetic Algorithm can be used to find the best path for autonomous mobile robots.
    • Genetic Algorithm can be used to find the optimal value for time of recharging.
    • Genetic Algorithm can be used for Automatic Recharging Path Planning for Cleaning Robots.

    General implementation of the Genetic Algorithm

    • This is a general implementation of the Genetic Algorithm.

    Types of search algorithms

    • Search algorithms can be classified into two categories: uninformed (Blind search) and informed search (Heuristic search).
    • Uninformed search does not contain any domain knowledge and operates in a brute-force way.
    • Informed search uses domain knowledge to guide the search.
    • Uninformed search only includes information about how to traverse the tree and how to identify leaf and goal nodes.
    • It is also called blind search.

    A* Search Algorithm

    • A* search algorithm is optimal if it is admissible and consistent.
    • Admissible heuristic is optimistic in nature.
    • Consistency is required for A* graph-search.
    • Time complexity of A* search algorithm depends on the heuristic function and the number of nodes expanded.
    • Space complexity of A* search algorithm is O(b^d)f(n).

    Using a Genetic Algorithm to Explore A*-like Path Finding Algorithms

    • The parameters of A* search are considered as chromosome parameters for Genetic Algorithm population.
    • The final solution path is found using iteration and expansion of nodes.
    • Time complexity of Greedy best-first search is O(bm).
    • Space complexity of Greedy best-first search is O(bm).
    • Greedy best-first search is incomplete and not optimal.

    A* Search Algorithm

    • A* search uses heuristic function h(n) and cost to reach the node n from the start state g(n).
    • The algorithm terminates when the goal node is found.
    • A* search algorithm is a combination of search heuristic and the cost to reach the node.
    • The algorithm uses a fitness number, which is the sum of the cost and heuristic function.
    • At each point in the search space, only the node with the lowest value of f(n) is expanded.
    • The algorithm follows a step-by-step process to find the goal node.

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    Description

    This quiz covers the use of Genetic Algorithm in the field of robotics, including its applications and examples. It is part of a comprehensive course on Genetic Algorithm, covering topics from introduction to machine learning and medicine.

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