PPT-1 Informed (Heuristic) Search Idea: be smart about what paths

1 Informed Heuristic Search Idea be smart about what paths to try 2 Blind Search vs Informed Search Whats the difference How do we formally specify this A node is selected for expansion based on an evaluation function that estimates cost to goal. Heuristic - a “rule of thumb” used to help guide search. often, something learned experientially and recalled when needed. Heuristic Function - function applied to a state in a search space to indicate a likelihood of success if that state is selected. This lecture topic. Read Chapter 3.5-3.7. Next lecture topic. Read Chapter 4.1-4.2. (Please read lecture topic material . before. and . after each lecture on that topic). You will be expected to know. Feedback: Tutorial 1. Describing a state.. Entire state space vs. incremental development.. Elimination of children.. Closed and the solution path.. Generation of children – effects on search.. Heuristic Search. Idea: give the algorithm “hints” about the desirability of different states . Use an . evaluation function. . to rank nodes and select the most promising one for expansion. Greedy best-first search. Initialize. . the . frontier . using the . starting state. While the frontier is not empty. Choose a frontier node to expand according to . search strategy . and take it off the frontier. If the node contains the . Initialize. . the . frontier . using the . starting state. While the frontier is not empty. Choose a frontier node to expand according to . search strategy . and take it off the frontier. If the node contains the . Heuristic - a “rule of thumb” used to help guide search. often, something learned experientially and recalled when needed. Heuristic Function - function applied to a state in a search space to indicate a likelihood of success if that state is selected. Problems. CSD 15-780: Graduate Artificial Intelligence. Instructors: . Zico. . Kolter. and Zack Rubinstein. TA: Vittorio . Perera. 2. Example of a search tree. . 3. How to Improve Search?. Avoid repeated states.. . the . frontier . using the . starting state. While the frontier is not empty. Choose a frontier node to expand according to . search strategy . and take it off the frontier. If the node contains the . . the . frontier . using the . starting state. While the frontier is not empty. Choose a frontier node to expand according to . search strategy . and take it off the frontier. If the node contains the . Winter 2018. Introduction to Artificial Intelligence. Prof. Richard Lathrop. Reading: R&N 3.5-3.7. Outline. Review limitations of uninformed search methods . Informed (or heuristic) search. Problem-specific heuristics to improve efficiency . Continued. Before we continue. Breadth-First. Depth-First. Uniform Cost. Iterative-Deepening. Before we continue. Breadth-First. S,A,B,D,C,G. Depth-First. S,A,C,D,B,G. Uniform Cost. S,A,B,D,C,G. Iterative-Deepening. Continued. Before We Start. HW1 extended to Monday. Submit online (now working) and bring paper print out. Questions?. Competency Demo next Wednesday. Study Guide Posted. We will have some discussion time on Monday. often, something learned experientially and recalled when needed. Heuristic Function - function applied to a state in a search space to indicate a likelihood of success if that state is selected. heuristic search methods are known as “weak methods” because of their generality and because they do not apply a great deal of knowledge .