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Page 1
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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