Assessing heuristic searches-artificial intelligence, Computer Engineering

Assessing Heuristic Searches

Given a specific problem you want to create an agent to solve, there can be more than one way of specifying it as a search problem, more than one option for the search strategy and different possibilities for heuristic measures. To a large extent, it is hard to predict what the best option will be, and it will require some experimentation to find out them. In some kind of cases, - if we calculate the effective branching rate, as described below - we may tell for sure if one heuristic measure is always being out-performed by another.

The Effective Branching Rate

Assessing heuristic functions is an essential part of Artificial Intelligence research: a specific heuristic function can sound like a good idea, but in practice give no discernible increase in the quality of the search. Search quality may be determined experimentally  in  terms  of  the  output  from  the  search,  and  by  using  sevral measures likewise  the effective branching rate. Imagine  a specific  problem P has been solved by search strategy S by expanding N nodes, and the solution lay at depth D in the space. Then the effective branching value of S for P is calculated by comparing S to a uniform search U. An example of a uniform search is a breadth first search where many branches from any node are always the same (as in our baby naming example). We then suppose the (uniform) branching rate of U is like  that, on exhausting its search to depth D, it too would have expanded defiantly N nodes. This imagined branching rate, written b*, is the effective branching rate of S and is calculated thus:

N = 1 + b* + (b*)2 + ... + (b*)D.

Rearranging this equation will give a value for b*. For an example (taken from  Norvig and Russell )imagine S finds a solution at depth 5 having expanded 52 nodes. In this type of case:

 52 = 1 + b* + (b*)2 + ... + (b*)5.

and it turns out that b*=1.91. To calculate its value , we use the well known mathematical identity:

 

This make us enables to write a polynomial for which b* is a 0, and we may solve this using numerical techniques such as Newton's method.

581_Assessing Heuristic Searches.png 
It is typically the case that the effective branching rate of a search strategy is same  over all the problems it is used for, because of this it is suitable to average b* over a small set of problems to give a valid account. If a heuristic search has a branching rate near to 1, then it is a good sign.  We say that 1 heuristic function  h1 dominates another h2 if the search using h1 always has a lower effective branching rate than h2. Having a lower effective branching rate is obviously desirable because it means a quicker search.

Posted Date: 10/2/2012 3:01:37 AM | Location : United States







Related Discussions:- Assessing heuristic searches-artificial intelligence, Assignment Help, Ask Question on Assessing heuristic searches-artificial intelligence, Get Answer, Expert's Help, Assessing heuristic searches-artificial intelligence Discussions

Write discussion on Assessing heuristic searches-artificial intelligence
Your posts are moderated
Related Questions
What is the type of Process Identifiers? Identification of the real user Identification of the effective user Identification of the real group Identification

Line A Line is, on a simple level, a mark connecting 2 points. However, how lines are used in an image is extremely important. By varying the quality of line used in an image,

I want to know...if there is a program available in C code using data structure for online movie booking system

One of the most important competitive strategies for E-Businesses today is business process reengineering. BPR is more than automating business processes to make modest improvement

What is an "on input filed" statements? ON INPUT The ABAP/4 module is known as only if a field having the Value other than the initial Value. This initial Value is explain

Q. Describe the Size and Speed of Scanners? Before actual scanning, a quick, low resolution scan known as pre-scan is made to preview the image and select scanning area. After

Define the Example Client-server Implementations Once you accept the client-server mindset, the process of architecting and developing applications becomes rather easy. Clearly

The next important effort in the direction of devising an electromechanical computer was made at Harvard University mutually sponsored by IBM and Department of UN Navy, Howard Aike

What are the features of Client/Server Computing? Although there are several different configurations, different hardware and software platforms and even dissimilar network pro

In order to calculate the performance of the program, the normal form of analysis of the program is to simply measure the total amount of CPU time needed to implement the various p