How is AI programming Different from Traditional Programming? by Subhajit Ghosh SignUp
Boloji.com
Boloji
Home Kabir Poetry Blogs BoloKids Writers Contribute Search Contact Site Map Advertise RSS Login Register
Boloji
Channels

In Focus

Analysis
Cartoons
Education
Environment
Going Inner
Opinion
Photo Essays

Columns

A Bystander's Diary
Business
My Word
PlainSpeak
Random Thoughts

Our Heritage

Architecture
Astrology
Ayurveda
Buddhism
Cinema
Culture
Dances
Festivals
Hinduism
History
People
Places
Sikhism
Spirituality
Vastu
Vithika

Society & Lifestyle

Family Matters
Health
Parenting
Perspective
Recipes
Society
Teens
Women

Creative Writings

Book Reviews
Ghalib's Corner
Humor
Individuality
Literary Shelf
Love Letters
Memoirs
Musings
Quotes
Ramblings
Stories
Travelogues
Workshop

Computing

CC++
Computing Articles
Flash
Internet Security
Java
Linux
Networking
Computing Articles Share This Page
How is AI programming Different
from Traditional Programming?
by Subhajit Ghosh Bookmark and Share
 

Most of us have already done a fair amount of traditional programming in languages like Pascal, C, Java or C++. We would devise algorithms (procedural steps) for solving the problem one is attempting to solve. Therefore, we would write code in the syntax of the specific High level language, and upon being error-free; our program is ready to provide solution to the problem. Give it an input, and it results in a desirable output. What is the limitation of this kind of problem solving? The problem solving steps in this case doesn’t need to interpret data meaningfully or to unravel hidden nuggets of information in the data (data mining).

AI programming is dynamic in comparison to the static nature of traditional programming. One need to incorporate intelligence, learning and knowledge while developing AI programming systems. Say in computationally hard problems in Computer Science like Chess Playing or Travelling Salesman Problem, it is impossible to code every possibility that may result in the form of rules and actions that may be taken thereof. The combinatorial explosion inherent in solving these types of problems would come in the way. In such cases, one may need to use intelligent guesses (heuristics) or optimizer based search methods (Genetic Algorithms, Simulated Annealing & others) to guide solutions towards an objective function i.e., goal.

Besides heuristic and guided search, AI programming often would need to make use of some of the following: Knowledge Acquisition and Representation, Pattern Recognition, Decision Making under Uncertainty, Machine Learning, Statistical Reasoning, Memory based Reasoning, Case Based Reasoning, Natural Language Understanding, Speech Synthesis, Image Understanding & Computer Vision, Logic Programming, a good Inference Engine & a developed Knowledge base.

11-Jun-2017
More by :  Subhajit Ghosh
 
Views: 14
 
Top | Computing Articles







A Bystander's Diary Analysis Architecture Astrology Ayurveda Book Reviews
Buddhism Business Cartoons CC++ Cinema Computing Articles
Culture Dances Education Environment Family Matters Festivals
Flash Ghalib's Corner Going Inner Health Hinduism History
Humor Individuality Internet Security Java Linux Literary Shelf
Love Letters Memoirs Musings My Word Networking Opinion
Parenting People Perspective Photo Essays Places PlainSpeak
Quotes Ramblings Random Thoughts Recipes Sikhism Society
Spirituality Stories Teens Travelogues Vastu Vithika
Women Workshop
RSS Feed RSS Feed Home | Privacy Policy | Disclaimer | Site Map
No part of this Internet site may be reproduced without prior written permission of the copyright holder.
Developed and Programmed by ekant solutions