# Lecture03HO - CS440/ECE448: Intro to Articial Intelligence!...

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Lecture 3: Systematic search Prof. Julia Hockenmaier juliahmr@illinois.edu http://cs.illinois.edu/fa11/cs440 CS440/ECE448: Intro to ArtiFcial Intelligence Review Different kinds of agents: re±ex-based, model-based, goal-based, utility-based, learning-based How do we evaluate agents? External performance measure What is the task environment like: observable?, known?, deterministic? sequential?, static? When is an agent rational? Answer 1: When an agent chooses actions that bring it closer to the goal. Answer 2: When an agent chooses actions that it expects to bring it closer to the goal Answer 2 is correct. 3 CS440/ECE448: Intro AI Problem solving as search

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Problem solving as search Problem solving Finding any solution ( goal-driven ) Finding the cheapest solution ( utility-driven ) Uninformed (blind) search (goal-driven): Algorithms: breadth-frst; depth-frst Informed (heuristic) search (utility-driven): Search costs; admissible heuristics Algorithms: greedy best frst; A* search 5 CS440/ECE448: Intro AI Problem solving The 8 queens problem Can you place 8 queens on a chess board so that they don ʼ t attack each other? ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! This doesn’t work! Phew! Initial State Goal Four possible actions: MoveTileUp MoveTileDown MoveTileLe±t MoveTileRight The 8-puzzle 8 4 8 2 1 6 5 3 7 1 2 3 4 5 6 7 8
Find a letter/digit substitution that forms a send + more = money forty ten + ten = sixty Cryptarithmetic The route-fnding problem Giurgiu Urziceni Hirsova Eforie Neamt Oradea Zerind Arad Timisoara Lugoj Mehadia Drobeta Craiova Sibiu Fagaras Pitesti Vaslui Iasi Rimnicu Vilcea Bucharest 71 75 118 111 70 75 120 151 140 99 80 97 101 211 138 146 85 90 98 142 92 87 86 Starting point Destination This lecture: assumptions Today ʼ s methods work when the environment is: 1. observable (Agent perceives all it needs to know) 2. known (Agent knows the effects of each action) 3. deterministic (Each action always has the same outcome) In such environments, the solution to any problem is a fxed sequence oF actions . Solving a problem 1. Formulate a goal goal = a (set of) state(s) to be in 2. De±ne the corresponding problem problem = what actions and states to consider 3. Find the solution to the problem solution = a sequence of actions to reach goal 4. Execute the solution

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Implementing problem solving We need: - a data structure to represent states - a designated initial state - a function that maps states to states
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## This note was uploaded on 10/13/2011 for the course CS 440 taught by Professor Levinson,s during the Spring '08 term at University of Illinois, Urbana Champaign.

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Lecture03HO - CS440/ECE448: Intro to Articial Intelligence!...

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