Artificial Inteligence

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Author:
finmcoul
ID:
290336
Filename:
Artificial Inteligence
Updated:
2014-12-02 06:13:50
Tags:
AI F29AI
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Description:
Revision for F29AI
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  1. Planning Agent
    • Uses abstract model of thee world
    • asks what if
    • Has goal to test conditions against
    • considers what the world would be
  2. Reflex Agent
    • Don't consider consequences
    • Choose action based on current percept
    • Consider what the world is
  3. Breadth First Search
    • Expands the shallowest nodes first
    • Fringe implemented as FIFO
  4. Depth First Search
    • Expands deepest node first
    • Fringe implemented as LIFO
    • Ties are alphabetically broken
  5. Uniform Cost Search
    • For structures with weights/costs
    • Expands all paths from starting node
    • Expands cheapest node path first
  6. Types of Search Heuristics
    • Manhattan Distance
    • Euclidean Distance
  7. A* Search
    • Uniform-cost orders by path cost g(n)
    • Greedy orders by proximity h(n)

    • For heuristic h and actual cost g
    • A* is for any node n
    • f(n) = g(n) + h(n)
  8. Admissible Heuristics
    • A heuristic is admissible if it is larger than the actual value
    • A heuristic h is admissible (optimistic) if:
    • h(n)≤h*(n)
    • where h*(n) is the true cost to a nearest goal
  9. Alpha-Beta Pruning
    Alpha–beta pruning is a search algorithm that seeks to decrease the number of nodes that are evaluated by the minimax algorithm in its search tree.
  10. Expectimax

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