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EA C461 Artificial Intelligence Uninformed Search Strategies

VimalEA C461- Artificial Intelligence. To discuss

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EA C461 Artificial Intelligence Uninformed Search Strategies

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    1. S.P.Vimal http://discovery.bits-pilani.ac.in/~vimalsp/1910AI/ EA C461 – Artificial Intelligence Uninformed Search Strategies

    2. Vimal EA C461- Artificial Intelligence To discuss… Best First Search Greedy Best First Search A* Search Heuristics, Design Issues Memory Bounded Search

    3. Vimal EA C461- Artificial Intelligence Introduction Search Heuristic / Informed Uses additional information about nodes (heuristics) that have not yet been explored to decide which nodes to examine next Blind / Uninformed Assumes no additional information about the problem Heuristic function h (n) used in search provides an estimate of the distance from any given node to a goal node

    4. Vimal EA C461- Artificial Intelligence Best First Search A node is selected for expansion based on an evaluation function f(n) Choose the node which appears to be best while expanding Best First Search algorithms differs in the evaluation function Evaluation function incorporate the problem specific knowledge in the form of h(n) h(n) ? heuristic function , a component of f(n) ? Estimated cost of cheapest path to the goal node h(n) = 0, if n is the goal node Greedy Best First Search, A* Search

    5. Vimal EA C461- Artificial Intelligence Greedy best-first search Expands the node that is closest to the goal Consider route finding problem in Romania Use of hSLD, Straight Line Distance Heuristic Evaluation function f(n) = h(n) (heuristic), estimate of cost from n to goal For the problem of finding route from Arad to Burcharest…

    6. Vimal EA C461- Artificial Intelligence

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