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RC Chakraborty, www.myreaders.info

 
 
        Artificial Intelligence - Introduction :   AI Course Lecture 1- 6,  notes, slides 
    www.myreaders.info/  ,  RC Chakraborty,  e-mail  rcchak@gmail.com ,  June 01, 2010 
www.myreaders.info/html/artificial_intelligence.html 
 
         
 
 
 
 
Introduction 
 
Artificial Intelligence 
 
 
www.myreaders.info
Return to Website
Introduction to Artificial Intelligence, topics : Definitions, goals, 
approaches, techniques, and branches; Intelligent behavior, 
understanding AI, hard or strong AI, soft or weak AI, cognitive 
science. General, engineering and science based AI Goals. AI 
approaches - cognitive science, laws of thought, turing test, rational 
agent. AI Techniques that make system to behave as intelligent - 
describe and match, goal reduction, constraint satisfaction, tree 
searching, generate and test, rule based systems. Biology-inspired AI 
techniques - neural networks, genetic algorithms, reinforcement 
learning.  Branches of AI - logical AI, search in AI, pattern recognition, 
knowledge representation, inferencing, common sense knowledge and 
reasoning, learning, planning, epistemology, ontology, heuristics, 
genetic programming. Applications of AI - game playing, speech 
recognition, understanding natural language, computer vision, expert 
systems. 
Page 2


RC Chakraborty, www.myreaders.info

 
 
        Artificial Intelligence - Introduction :   AI Course Lecture 1- 6,  notes, slides 
    www.myreaders.info/  ,  RC Chakraborty,  e-mail  rcchak@gmail.com ,  June 01, 2010 
www.myreaders.info/html/artificial_intelligence.html 
 
         
 
 
 
 
Introduction 
 
Artificial Intelligence 
 
 
www.myreaders.info
Return to Website
Introduction to Artificial Intelligence, topics : Definitions, goals, 
approaches, techniques, and branches; Intelligent behavior, 
understanding AI, hard or strong AI, soft or weak AI, cognitive 
science. General, engineering and science based AI Goals. AI 
approaches - cognitive science, laws of thought, turing test, rational 
agent. AI Techniques that make system to behave as intelligent - 
describe and match, goal reduction, constraint satisfaction, tree 
searching, generate and test, rule based systems. Biology-inspired AI 
techniques - neural networks, genetic algorithms, reinforcement 
learning.  Branches of AI - logical AI, search in AI, pattern recognition, 
knowledge representation, inferencing, common sense knowledge and 
reasoning, learning, planning, epistemology, ontology, heuristics, 
genetic programming. Applications of AI - game playing, speech 
recognition, understanding natural language, computer vision, expert 
systems. 
RC Chakraborty, www.myreaders.info

 
Introduction 
 
Artificial Intelligence 
 
 
 
Topics  
(Lectures 01, 02, 03, 04, 05,  06      6 hours) 
 
 
 
Slides
1. Definitions  
Artificial Intelligence, Intelligence, Intelligent behavior, Understanding
AI,  Hard  or  Strong  AI,   Soft  or  Weak  AI,  Cognitive Science.  
 
03-10
2. Goals  of  AI  
General  AI  Goal,  Engineering based AI Goal,  Science based AI Goal. 
 
11-12
3. AI  Approaches  
Cognitive science,  Laws of thought,  Turing Test,  Rational agent. 
 
13-16
4. AI  Techniques  
Techniques  that make system to behave as Intelligent  
Describe and match, Goal reduction, Constraint satisfaction, Tree 
Searching, Generate and test, Rule based systems,  
Biology-inspired AI techniques  
Neural Networks, Genetic Algorithms, Reinforcement learning. 
 
17-32
5. Branches  of  AI  
Logical AI, Search in AI, Pattern Recognition, Knowledge Representation, 
Inference, Common sense knowledge and reasoning, Learning, Planning, 
Epistemology, Ontology, Heuristics, Genetic programming. 
  
33-45
6. Applications of AI  
Game playing, Speech Recognition, Understanding Natural Language, 
Computer Vision, Expert Systems.  
 
46-50
7. References  
 
51 
02 
     
 
Page 3


RC Chakraborty, www.myreaders.info

 
 
        Artificial Intelligence - Introduction :   AI Course Lecture 1- 6,  notes, slides 
    www.myreaders.info/  ,  RC Chakraborty,  e-mail  rcchak@gmail.com ,  June 01, 2010 
www.myreaders.info/html/artificial_intelligence.html 
 
         
 
 
 
 
Introduction 
 
Artificial Intelligence 
 
 
www.myreaders.info
Return to Website
Introduction to Artificial Intelligence, topics : Definitions, goals, 
approaches, techniques, and branches; Intelligent behavior, 
understanding AI, hard or strong AI, soft or weak AI, cognitive 
science. General, engineering and science based AI Goals. AI 
approaches - cognitive science, laws of thought, turing test, rational 
agent. AI Techniques that make system to behave as intelligent - 
describe and match, goal reduction, constraint satisfaction, tree 
searching, generate and test, rule based systems. Biology-inspired AI 
techniques - neural networks, genetic algorithms, reinforcement 
learning.  Branches of AI - logical AI, search in AI, pattern recognition, 
knowledge representation, inferencing, common sense knowledge and 
reasoning, learning, planning, epistemology, ontology, heuristics, 
genetic programming. Applications of AI - game playing, speech 
recognition, understanding natural language, computer vision, expert 
systems. 
RC Chakraborty, www.myreaders.info

 
Introduction 
 
Artificial Intelligence 
 
 
 
Topics  
(Lectures 01, 02, 03, 04, 05,  06      6 hours) 
 
 
 
Slides
1. Definitions  
Artificial Intelligence, Intelligence, Intelligent behavior, Understanding
AI,  Hard  or  Strong  AI,   Soft  or  Weak  AI,  Cognitive Science.  
 
03-10
2. Goals  of  AI  
General  AI  Goal,  Engineering based AI Goal,  Science based AI Goal. 
 
11-12
3. AI  Approaches  
Cognitive science,  Laws of thought,  Turing Test,  Rational agent. 
 
13-16
4. AI  Techniques  
Techniques  that make system to behave as Intelligent  
Describe and match, Goal reduction, Constraint satisfaction, Tree 
Searching, Generate and test, Rule based systems,  
Biology-inspired AI techniques  
Neural Networks, Genetic Algorithms, Reinforcement learning. 
 
17-32
5. Branches  of  AI  
Logical AI, Search in AI, Pattern Recognition, Knowledge Representation, 
Inference, Common sense knowledge and reasoning, Learning, Planning, 
Epistemology, Ontology, Heuristics, Genetic programming. 
  
33-45
6. Applications of AI  
Game playing, Speech Recognition, Understanding Natural Language, 
Computer Vision, Expert Systems.  
 
46-50
7. References  
 
51 
02 
     
 
RC Chakraborty, www.myreaders.info

 
 
Introduction 
 
 
 What  is  Artificial  Intelligence ? 
 
 
• 
John McCarthy, who coined the term Artificial Intelligence in 1956, 
defines it as "the science and engineering of making intelligent 
machines",  especially  intelligent  computer  programs. 
 
 
• 
Artificial Intelligence (AI) is the intelligence of machines and the branch 
of  computer science  that  aims  to  create  it. 
 
 
• 
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. 
 
 
• 
AI is the study of the mental faculties through the use of 
computational  models. 
  
 
• 
AI  is the study of  :  How  to  make  computers  do  things  which,  at  the 
moment,  people  do  better. 
 
 
• 
AI is the study and design of intelligent agents, where an intelligent 
agent is a system that perceives its environment and takes actions 
that  maximize  its  chances  of  success.  
03      
 
Page 4


RC Chakraborty, www.myreaders.info

 
 
        Artificial Intelligence - Introduction :   AI Course Lecture 1- 6,  notes, slides 
    www.myreaders.info/  ,  RC Chakraborty,  e-mail  rcchak@gmail.com ,  June 01, 2010 
www.myreaders.info/html/artificial_intelligence.html 
 
         
 
 
 
 
Introduction 
 
Artificial Intelligence 
 
 
www.myreaders.info
Return to Website
Introduction to Artificial Intelligence, topics : Definitions, goals, 
approaches, techniques, and branches; Intelligent behavior, 
understanding AI, hard or strong AI, soft or weak AI, cognitive 
science. General, engineering and science based AI Goals. AI 
approaches - cognitive science, laws of thought, turing test, rational 
agent. AI Techniques that make system to behave as intelligent - 
describe and match, goal reduction, constraint satisfaction, tree 
searching, generate and test, rule based systems. Biology-inspired AI 
techniques - neural networks, genetic algorithms, reinforcement 
learning.  Branches of AI - logical AI, search in AI, pattern recognition, 
knowledge representation, inferencing, common sense knowledge and 
reasoning, learning, planning, epistemology, ontology, heuristics, 
genetic programming. Applications of AI - game playing, speech 
recognition, understanding natural language, computer vision, expert 
systems. 
RC Chakraborty, www.myreaders.info

 
Introduction 
 
Artificial Intelligence 
 
 
 
Topics  
(Lectures 01, 02, 03, 04, 05,  06      6 hours) 
 
 
 
Slides
1. Definitions  
Artificial Intelligence, Intelligence, Intelligent behavior, Understanding
AI,  Hard  or  Strong  AI,   Soft  or  Weak  AI,  Cognitive Science.  
 
03-10
2. Goals  of  AI  
General  AI  Goal,  Engineering based AI Goal,  Science based AI Goal. 
 
11-12
3. AI  Approaches  
Cognitive science,  Laws of thought,  Turing Test,  Rational agent. 
 
13-16
4. AI  Techniques  
Techniques  that make system to behave as Intelligent  
Describe and match, Goal reduction, Constraint satisfaction, Tree 
Searching, Generate and test, Rule based systems,  
Biology-inspired AI techniques  
Neural Networks, Genetic Algorithms, Reinforcement learning. 
 
17-32
5. Branches  of  AI  
Logical AI, Search in AI, Pattern Recognition, Knowledge Representation, 
Inference, Common sense knowledge and reasoning, Learning, Planning, 
Epistemology, Ontology, Heuristics, Genetic programming. 
  
33-45
6. Applications of AI  
Game playing, Speech Recognition, Understanding Natural Language, 
Computer Vision, Expert Systems.  
 
46-50
7. References  
 
51 
02 
     
 
RC Chakraborty, www.myreaders.info

 
 
Introduction 
 
 
 What  is  Artificial  Intelligence ? 
 
 
• 
John McCarthy, who coined the term Artificial Intelligence in 1956, 
defines it as "the science and engineering of making intelligent 
machines",  especially  intelligent  computer  programs. 
 
 
• 
Artificial Intelligence (AI) is the intelligence of machines and the branch 
of  computer science  that  aims  to  create  it. 
 
 
• 
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. 
 
 
• 
AI is the study of the mental faculties through the use of 
computational  models. 
  
 
• 
AI  is the study of  :  How  to  make  computers  do  things  which,  at  the 
moment,  people  do  better. 
 
 
• 
AI is the study and design of intelligent agents, where an intelligent 
agent is a system that perceives its environment and takes actions 
that  maximize  its  chances  of  success.  
03      
 
RC Chakraborty, www.myreaders.info

 AI - Definitions 
1. Definitions  
 1.1 Artificial Intelligence (AI)  
 
 
 
The definitions of AI outlined in textbooks   
   
(a) 
'The exciting new effort to make 
computers think ... machines with
minds, in the full and literal sense' 
(Haugeland, 1985) 
  
'The automation of activities that we 
associate with human thinking, 
activities such as decision-making, 
problem solving, learning ...'
(Bellman, 1978) 
 
(b)
'The study of mental faculties through 
the use of computational models'
(Charniak and McDermott, 1985) 
  
 
'The study of the computations that 
make it possible to perceive, reason, 
and act' (Winston, 1992)  
 
(C) 
'The art of creating machines that 
perform functions that require 
intelligence when performed by 
people' (Kurzweil, 1990)  
 
'The study of how to make computers 
do things at which, at the moment, 
people are better' (Rich and Knight, 
1991)  
 
(d)
'A field of study that seeks to explain 
and emulate intelligent behavior in 
terms of computational processes'
(Schalkoff, 1990) 
  
'The branch of computer science that 
is concerned with the automation of 
intelligent behavior' (Luger and 
Stubblefield, 1993)  
 
     
 
 
? The definitions on the top,  
(a) and (b) are concerned with reasoning, whereas those on the bottom,
(c) and (d) address behavior.  
 
? The definitions on the left,   
(a) and (c) measure success in terms of human performance, whereas 
those on the right,  
(b) and  (d) measure ideal concept of intelligence called rationality.  
Note :   A  system  is  rational  if  it does  the  right  thing.  
04      
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FAQs on 01 Introduction to Artificial Intelligence - Computer Science Engineering (CSE)

1. What is artificial intelligence in computer science?
Ans. Artificial intelligence (AI) in computer science refers to the development of computer systems that can perform tasks that typically require human intelligence. It involves creating intelligent machines that can simulate human behavior, such as speech recognition, problem-solving, learning, and decision-making.
2. What are the applications of artificial intelligence in computer science?
Ans. Artificial intelligence has various applications in computer science, including: - Natural language processing: AI enables computers to understand and interpret human language, which is useful in chatbots, voice assistants, and language translation. - Machine learning: AI algorithms can learn and improve from experience, making it useful in areas like image recognition, fraud detection, and recommendation systems. - Robotics: AI is used in designing intelligent robots that can perform tasks autonomously, such as manufacturing, healthcare, and exploration. - Expert systems: AI can be used to create systems that mimic human expertise, helping in areas like medical diagnosis, financial analysis, and risk assessment.
3. What are the benefits of studying artificial intelligence in computer science?
Ans. Studying artificial intelligence in computer science offers several benefits, including: - Career opportunities: AI is a rapidly growing field with a high demand for professionals. By studying AI, you can explore various career paths in industries like healthcare, finance, gaming, and robotics. - Problem-solving skills: AI involves developing algorithms to solve complex problems, which enhances your analytical and critical thinking abilities. - Innovation and creativity: AI encourages you to think outside the box and come up with innovative solutions to challenges. - Understanding technology: AI is becoming increasingly integrated into our daily lives, and studying it helps you understand the technology behind applications like voice assistants, autonomous vehicles, and smart home devices.
4. What are the challenges in implementing artificial intelligence in computer science?
Ans. Implementing artificial intelligence in computer science faces several challenges, including: - Data availability and quality: AI algorithms require large amounts of high-quality data for training. Obtaining such data can be difficult and time-consuming. - Ethical concerns: AI raises ethical questions, such as privacy, bias, and job displacement. Ensuring responsible and unbiased AI systems is a challenge. - Computing power: AI algorithms often require significant computational resources, making it challenging to implement them on low-power devices. - Explainability: Some AI models, such as deep learning neural networks, are often considered "black boxes" as they are difficult to interpret. This lack of explainability poses challenges in critical applications like healthcare and finance.
5. How can artificial intelligence impact society and everyday life?
Ans. Artificial intelligence has the potential to greatly impact society and everyday life in various ways, including: - Automation of tasks: AI can automate repetitive and mundane tasks, freeing up human resources for more complex and creative work. - Improved healthcare: AI can assist in medical diagnosis, drug discovery, and personalized treatment plans, leading to improved healthcare outcomes. - Enhanced safety and security: AI can be used for surveillance, threat detection, and fraud prevention, making society safer. - Personalized user experiences: AI algorithms can analyze user data and provide personalized recommendations, leading to customized experiences in areas like entertainment, shopping, and social media. - Transportation and mobility: AI is driving advancements in autonomous vehicles, traffic management, and logistics, which can improve transportation efficiency and safety.
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