PPT-Uninformed (also called blind) search algorithms

This Lecture Read Chapter 3134 Next Lecture Read Chapter 3537 Please read lecture topic material before and after each lecture on that topic You will be expected to know Overview of uninformed search methods. Jim Little. UBC CS 322 – Search . 2. September . 12, . 2014. Textbook . §. 3.5. 1. CPSC 322, Lecture 4. Slide . 2. Search. is a key computational mechanism in many . AI agents . We will study the basic principles of search on the simple . Chapter 4. Local search algorithms. Hill-climbing search. Simulated annealing search. Local beam search. Genetic algorithms. Outline. In many optimization problems, the . path. to the goal is irrelevant; the goal state itself is the . Problem-solving agents. Example: Romania. On holiday in Romania; currently in Arad. .. Flight leaves tomorrow from . Bucharest. What do we need to define?. Problem Formulation. The process of defining actions, states and goal.. Want to go from Arad to Bucharest = many ways to go. Level 1 choice is . Zerind. , Sibiu, Timisoara. If you went to . Zerind. , then next blind choice would be . Odarea. of back to Arad – inefficient you started over – could use this to eliminate that choice. A . search strategy . is defined by picking the order of node . expansion. Uninformed. . search strategies use only the information available in the problem . definition. Breadth-first search. Depth-first search. A . search strategy . is defined by picking the order of node . expansion. Uninformed. . search strategies use only the information available in the problem . definition. Breadth-first search. Depth-first search. Xiao Zhang. 1. , Wang-Chien Lee. 1. , Prasenjit Mitra. 1, 2. , Baihua Zheng. 3. 1. Department of Computer Science and Engineering. 2. College of Information Science and Technology. The Pennsylvania State University. Uninformed (Blind) Search Algorithms. Project 1 is out, check class homepage. Due in two weeks 9/27/2010 Monday before class. Projects for students in different groups (480/580/796) could be different later on. A . search strategy . is defined by picking the order of node . expansion. Uninformed. . search strategies use only the information available in the problem . definition. Breadth-first search. Depth-first search. Said. about the Scriptures vs. What is . Written. There. A . Watchman at the Gate . Call . . . to . Put . Aside Tradition . . . In Exchange for What . is Written. By Barbara L. Klika, MSW. (Section 3.4). Source: . Fotolia. Uninformed search strategies. A . search strategy . is defined by picking the order of node . expansion. Uninformed. . search strategies use only the information available in the problem . Simple Example. Refer to Excel Demo in Class . Example blind random parameter search code. Conceptual Example: Want to go from Arad to Bucharest = many ways to go. Level 1 choice is . Zerind. , Sibiu, Timisoara. Some material adopted from notes by Charles R. Dyer, University of Wisconsin-Madison. Today’. s topics. Goal-based agents. Representing states and actions. Example problems. Generic state-space search algorithm. Readings: [SG] Ch. 3. Chapter Outline:. Attributes of Algorithms. Measuring Efficiency of Algorithms. Simple Analysis of Algorithms. Polynomial vs Exponential Time Algorithms. Efficiency of Algorithms .