SP11 cs188 lecture 3 -- a-star search 6PP

SP11 cs188 lecture 3 -- a-star search 6PP - CS 188:...

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1 CS 188: Artificial Intelligence Fall 2009 Lecture 3: A* Search 9/3/2009 Pieter Abbeel – UC Berkeley Many slides from Dan Klein Search Gone Wrong? Announcements s Assignments: s Project 0 (Python tutorial): due Friday 1/28 at 4:59pm s Project 1 (Search): due Friday 2/4 at 4:59pm s Watch for office hour specifics --- GSI project Czar! s Still looking for project partners? --- Come to front after lecture. s Try pair programming, not divide-and-conquer s Account forms available up front during break and after lecture s Lecture Videos: will be linked from lecture schedule s Sections start tomorrow s Have fun solving exercises! Solutions will be posted online on Friday after last section. s After 2 weeks of section we will evaluate potential overcrowdedness issues and find a solution Today s Time and space complexity of DFS and BFS s Iterative deepening --- “best of both worlds” s Uniform cost search s Greedy search s A* search s Heuristic design s Admissibility, Consistency s Tree search b Graph search Recap: Search s Search problem: s States (configurations of the world) s Successor function: a function from states to lists of (state, action, cost) triples; drawn as a graph s Start state and goal test s Search tree: s Nodes: represent plans for reaching states s Plans have costs (sum of action costs) s Search Algorithm: s Systematically builds a search tree s Chooses an ordering of the fringe (unexplored nodes) General Tree Search s Important ideas: s Fringe s Expansion s Exploration strategy s Main question: which fringe nodes to explore? Detailed pseudocode is in the book!
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2 Example Search Tree s Search: s Expand out possible plans s Maintain a fringe of unexpanded plans s Try to expand as few tree nodes as possible Search Algorithm Properties s Complete? Guaranteed to find a solution if one exists? s Optimal? Guaranteed to find the least cost path? s Time complexity? s Space complexity? Variables: n Number of states in the problem b The average branching factor B (the average number of successors) C* Cost of least cost solution s Depth of the shallowest solution m Max depth of the search tree DFS s Infinite paths make DFS incomplete… s How can we fix this? Algorithm Complete Optimal Time Space DFS Depth First Search N N O(B LMAX ) O(LMAX) START GOAL a b N N Infinite Infinite DFS s With cycle checking, DFS is complete.* s When is DFS optimal? Algorithm
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This note was uploaded on 08/26/2011 for the course CS 188 taught by Professor Staff during the Spring '08 term at University of California, Berkeley.

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SP11 cs188 lecture 3 -- a-star search 6PP - CS 188:...

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