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# chapter3 - Solving problems by searching 1 CHAPTER 3 CS...

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C H A P T E R 3 14 Jan 2004 CS 3243 - Blind Search 1 Solving problems by searching

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Outline 14 Jan 2004 CS 3243 - Blind Search 2 Problem-solving agents Problem types Problem formulation Example problems Basic search algorithms
Problem-solving agents 14 Jan 2004 CS 3243 - Blind Search 3 Note: this is offline problem solving; solution executed “eyes closed.”

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Example: Romania 14 Jan 2004 CS 3243 - Blind Search 4 On holiday in Romania; currently in Arad. Flight leaves tomorrow from Bucharest Formulate goal : be in Bucharest Formulate problem : states : various cities actions : drive between cities Find solution : sequence of cities, e.g., Arad, Sibiu, Fagaras, Bucharest
Example: Romania 14 Jan 2004 CS 3243 - Blind Search 5 Abstraction: The process of removing details from a representation Is the map a good representation of the problem? What is a good replacement?

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Problem types 14 Jan 2004 CS 3243 - Blind Search 6 Deterministic, fully observable single-state problem Agent knows exactly which state it will be in; solution is a sequence Vacuum world everything observed Romania The full map is observed Single-state: Start in #5. Solution?? [Right, Suck]
Problem types 14 Jan 2004 CS 3243 - Blind Search 7 Non-observable sensorless problem (conformant problem) Agent may have no idea where it is; solution is a sequence Vacuum world No sensors Romania No map just know operators(cities you can move to) Conformant: Start in {1, 2, 3, 4, 5, 6, 7, 8} e.g., Right goes to {2, 4, 6, 8}. Solution?? [Right, Suck,Left, Suck]

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Problem types 14 Jan 2004 CS 3243 - Blind Search 8 Nondeterministic and/or partially observable contingency problem percepts provide new information about current state Unknown state space exploration problem Vacuum world know state of current location Romania know current location and neighbor cities Contingency: [L,clean] Start in #5 or #7 Murphy’s Law: Suck can dirty a clean carpet Local sensing: dirt, location only. Solution?? [Right, if dirt then Suck]
Single-state problem formulation 14 Jan 2004 CS 3243 - Blind Search 9 A problem is defined by four items: 1. initial state e.g., "at Arad“ 2. actions or successor function S(x) = set of action state pairs e.g., S(Arad) = { <Arad Zerind, Zerind >, … } 3. goal test , can be explicit , e.g., x = "at Bucharest" implicit , e.g., Checkmate(x) 4. path cost (additive) e.g., sum of distances, number of actions executed, etc. c(x,a,y) is the step cost , assumed to be 0 A solution is a sequence of actions leading from the initial state to a goal state

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Selecting a state space 14 Jan 2004 CS 3243 - Blind Search 10 Real world is absurdly complex state space must be abstracted for problem solving
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chapter3 - Solving problems by searching 1 CHAPTER 3 CS...

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