22 September 2020
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Artificial Intelligence and Cognitive Computing: Introduction to Problem Solving, Assignments of Artificial Intelligence
THIS IS A AI LECTURE - MODULE1
Typology: Assignments
2019/2020
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1
Warm Welcome
to
All Budding Engineers of New Horizon College of Engineering
September
2 DEPARTMENT OF ELECTRONICS AND COMMUNICATION ENGINEERING
ONLINE LECTURES
FACULTY : SANTHOSH KRISHNA B V - Sr.Assist Professor
CLASS : IV ECE – VII SEM
SUB : ECE735- Artificial Intelligence & Cognitive Computing
UNIT : 1
Syllabus
**Text books: 1 .Artificial Intelligence, E.Rich, K.Knight & S.B.Nair, 3 e 2009 , Mcgraw Hill
- Cognitive Computing : Theory & Applications, Vijay V.Raghavan, 2016 , Elsevier**
UNIT 1- INTRODUCTION
Contents
❖Definition of Artificial Intelligence
❖Problems
❖ Problem spaces and Search
❖Heuristic Search Technique
What is AI :
Answer :
The power of a machine to copy intelligent human
behaviour
Right?
- There is no clear consensus on the definition of AI
- John McCarthy coined the phrase AI in 1956
AI- Definition
What is artificial intelligence?
It is the science and engineering of making intelligent machines,
especially intelligent computer programs. It is related to the
similar task of using computers to understand human
intelligence, but AI does not have to confine itself to methods
that are biologically observable.
Yes, but what is intelligence?
Intelligence is the computational part of the ability to achieve
goals in the world. Varying kinds and degrees of intelligence
occur in people, many animals and some machines.
Isn't there a solid definition of intelligence that doesn't
depend on relating it to human intelligence?
Not yet. The problem is that we cannot yet characterize in
general what kinds of computational procedures we want to call
intelligent. We understand some of the mechanisms of
intelligence and not others.
Working Definition :
Artificial intelligence is the study of how to make computers do things that
people are better at or would be better at if:
❖ they could extend what they do to a World Wide Web-sized amount
of data and
❖ not make mistakes.
Philosophy Logic, methods of reasoning, mind as physical system, foundations of learning, language, rationality. Mathematics Formal representation and proof, algorithms, computation, (un)decidability, (in)tractability, probability. Economics utility, decision theory Neuroscience neurons as information processing units. Psychology/ Cognitive Science how do people behave, perceive, process information, represent knowledge. Computer engineering building fast computers and programs Control theory design systems that maximize an objective function over time Linguistics knowledge representation, grammar
Academic Disciplines important to AI
AI Problems
❖ Game Playing
❖ Theorem Proving
❖ Common Sense Reasoning
❖ Perception ( Vision & Speech)
❖ Natural Language Understanding
Task Domains in AI
Applications of AI
AI has been dominant in various fields such as − Gaming − AI plays crucial role in strategic games such as chess, poker, tic-tac- toe, etc., where machine can think of large number of possible positions based on heuristic knowledge. Natural Language Processing − It is possible to interact with the computer that understands natural language spoken by humans. Expert Systems − There are some applications which integrate machine, software, and special information to impart reasoning and advising. They provide explanation and advice to the users.
22 September 2020 17 Vision Systems − These systems understand, interpret, and comprehend visual input on the computer. For example, ❖A spying aeroplane takes photographs, which are used to figure out spatial information or map of the areas. ❖Doctors use clinical expert system to diagnose the patient. ❖Police use computer software that can recognize the face of criminal with the stored portrait made by forensic artist.
. Speech Recognition − Some intelligent systems are capable of hearing and comprehending the language in terms of sentences and their meanings while a human talks to it. It can handle different accents, slang words, noise in the background, change in human’s noise due to cold, etc. Applications of AI- Contd...
19 Requirements for AI problems and solution techniques
AI problems and solution techniques requires :
➢ Understanding assumption about intelligence
➢ Techniques for solving AI problems
➢ Level to model Human Intelligence
➢ Criteria for Success
i. Understanding assumption about intelligence The underlying assumption is Physical symbol system hypothesis. A physical symbol system (also called a formal system) takes physical patterns (symbols), combining them into structures (expressions) and manipulating them (using processes) to produce new expressions.