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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 square4 Assignments: square4 Project 0 (Python tutorial): due Friday 1/28 at 4:59pm square4 Project 1 (Search): due Friday 2/4 at 4:59pm square4 Watch for office hour specifics --- GSI project Czar! square4 Still looking for project partners? --- Come to front after lecture. square4 Try pair programming, not divide-and-conquer square4 Account forms available up front during break and after lecture square4 Lecture Videos: will be linked from lecture schedule square4 Sections start tomorrow square4 Have fun solving exercises! Solutions will be posted online on Friday after last section. square4 After 2 weeks of section we will evaluate potential overcrowdedness issues and find a solution Today square4 Time and space complexity of DFS and BFS square4 Iterative deepening --- “best of both worlds” square4 Uniform cost search square4 Greedy search square4 A* search square4 Heuristic design square4 Admissibility, Consistency square4 Tree search barb2right Graph search Recap: Search square4 Search problem: square4 States (configurations of the world) square4 Successor function: a function from states to lists of (state, action, cost) triples; drawn as a graph square4 Start state and goal test square4 Search tree: square4 Nodes: represent plans for reaching states square4 Plans have costs (sum of action costs) square4 Search Algorithm: square4 Systematically builds a search tree square4 Chooses an ordering of the fringe (unexplored nodes) General Tree Search square4 Important ideas: square4 Fringe square4 Expansion square4 Exploration strategy square4 Main question: which fringe nodes to explore? Detailed pseudocode is in the book!
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2 Example Search Tree square4 Search: square4 Expand out possible plans square4 Maintain a fringe of unexpanded plans square4 Try to expand as few tree nodes as possible Search Algorithm Properties square4 Complete? Guaranteed to find a solution if one exists? square4 Optimal? Guaranteed to find the least cost path? square4 Time complexity? square4 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 square4 Infinite paths make DFS incomplete… square4 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 square4 With cycle checking, DFS is complete.* square4 When is DFS optimal?
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SP11 cs188 lecture 3 -- a-star search 6PP - CS 188...

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