PPT-Heuristic search, A* CS171,

Winter 2018 Introduction to Artificial Intelligence Prof Richard Lathrop Reading RampN 3537 Outline Review limitations of uninformed search methods Informed or heuristic search Problemspecific heuristics to improve efficiency . 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. 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. . 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 . . 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 . 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. 1 Informed (Heuristic) Search Idea: be smart about what paths to try. 2 Blind Search vs. Informed Search What’s the difference? How do we formally specify this? A node is selected for expansion based on an evaluation function that estimates cost to goal. 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 .