Lesson 05 - Module 2 Problem Solving using Search(Single...

Info iconThis preview shows pages 1–5. Sign up to view the full content.

View Full Document Right Arrow Icon
Module 2 Problem Solving using Search- (Single agent search) Version 1 CSE IIT, Kharagpur
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
Lesson 5 Informed Search Strategies-I Version 1 CSE IIT, Kharagpur
Background image of page 2
3.1 Introduction We have outlined the different types of search strategies. In the earlier chapter we have looked at different blind search strategies. Uninformed search methods lack problem- specific knowledge. Such methods are prohibitively inefficient in many cases. Using problem-specific knowledge can dramatically improve the search speed. In this chapter we will study some informed search algorithms that use problem specific heuristics. Review of different Search Strategies 1. Blind Search a) Depth first search b) Breadth first search c) Iterative deepening search d) Bidirectional search 2. Informed Search 3.1.1 Graph Search Algorithm We begin by outlining the general graph search algorithm below. Graph search algorithm Let fringe be a list containing the initial state Let closed be initially empty Loop if fringe is empty return failure Node Å remove-first ( fringe ) if Node is a goal then return the path from initial state to Node else put Node in closed generate all successors of Node S for all nodes m in S if m is not in fringe or closed merge m into fringe End Loop 3.1.2 Review of Uniform-Cost Search (UCS) We will now review a variation of breadth first search we considered before, namely Uniform cost search. To review, in uniform cost search we enqueue nodes by path cost. Let g(n) = cost of the path from the start node to the current node n. Version 1 CSE IIT, Kharagpur
Background image of page 3

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
The algorithm sorts nodes by increasing value of g, and expands the lowest cost node of the fringe. Properties of Uniform Cost Search Complete Optimal/Admissible Exponential time and space complexity, O(bd) The UCS algorithm uses the value of g(n) to select the order of node expansion. We will now introduce informed search or heuristic search that uses problem specific heuristic information. The heuristic will be used to select the order of node expansion. 3.1.3 Informed Search We have seen that uninformed search methods that systematically explore the state space and find the goal. They are inefficient in most cases. Informed search methods use problem specific knowledge, and may be more efficient. At the heart of such algorithms there is the concept of a heuristic function. 3.1.3.1 Heuristics Heuristic means “rule of thumb”. To quote Judea Pearl, “Heuristics are criteria, methods or principles for deciding which among several alternative courses of action promises to be the most effective in order to achieve some goal”. In heuristic search or informed search, heuristics are used to identify the most promising search path. Example of Heuristic Function
Background image of page 4
Image of page 5
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}

Page1 / 15

Lesson 05 - Module 2 Problem Solving using Search(Single...

This preview shows document pages 1 - 5. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online