5 UNINFORMED SEARCH

# 5 UNINFORMED SEARCH - UNI NFORMED SEARCH An uninformed...

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Unformatted text preview: UNI NFORMED SEARCH An uninformed search algorithm is one that does not take into account the specific nature of the problem. As such, they can be implemented in general, and then the same implementation can be used in a wide range of problems. The drawback is that most search spaces are extremely large, and an uninformed search (especially of a tree) will take a reasonable amount of time only for small examples Uninfor med sear ch on tr ees • Uninformed means we only know: • 1. The goal test • 2. The succs() function • But not which non-goal states are better: informed search (next lecture). • For now, we also assume succs() gr aph is acyclic. • Won’t encounter repeated states. • The graph is a tree. • We will relax it later. • Search strategies: BFS, UCS, DFS, I DS. • Differ by what un-expanded nodes to expand Per for mance of sear ch algor ithms on tr ees THI NGS TO DECI DE • 1. Actions • 2. State Descriptions • 3. Goal state Examples: Water Jug Pr oblem • Given a 5-gallon jug and a 2-gallon jug, with the 5- gallon jug initially full of water and the 2-gallon jug empty, the goal is to fill the 2-gallon jug with exactly one gallon of water. – State = (x,y), where x = number of gallons of water in the 5-gallon jug and y is gallons in the 2-gallon jug – I nitial State = (5,0) – Goal State = (*,1), where * means any amount – Operators • (x,y) -> (0,y) ; empty 5-gal jug • (x,y) -> (x,0) ; empty 2-gal jug • (x,2) and x<=3 -> (x+2,0) ; pour 2-gal into 5-gal •...
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5 UNINFORMED SEARCH - UNI NFORMED SEARCH An uninformed...

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