Artificial Intelligence Lab programs 1. Write a Program to Implement

AI

1. BCS515B ARTIFICIAL INTELLIGENCE

2. Module – 1 Introduction: What Is AI? The State of The Art. Intelligent Agents: Agents and environment, Concept of Rationality, The nature of environment, The structure of agents. Stuart J. Russell and Peter Norvig, Artificial Intelligence 3 rd Pearson 2015

3. Artificial –man made Intelligence- thinking power Branch of CS which we can create a intelligent m/c which can behave like human , think like human and able to make decision AI, no need to preprogram machine to do some task Create a m/c with programmed algorithm which can work with own intelligence.

4. Why AI Artificial intelligence (AI) makes it possible for machines to learn from experience , adjust to new inputs and perform human-like tasks. Most AI examples Chess-playing computers( Garry Kasparov-IBM-DEEP BLUE) to self-driving cars(TESLA) – rely heavily on deep learning and  natural language processing . Using these technologies , computers can be trained to accomplish specific tasks by processing large amounts of data and recognizing patterns in the data. 4

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6. Reasons behind why learn AI: Bright career- Decent Salary - work as a Machine Learning Engineer, Data Scientist, Business Intelligence Developer, Research Engineer AI i s versatile-  It is applicable to any industry -healthcare, automobile, and even banking and finance sector. for example ,   PathAI , which is a technology that will assist pathologists in reducing error rates in cancer diagnosis Skill of the century -create many and different job opportunities in related fields. Ingests huge amounts of data -Humans generate more than 2.5 quintillion bytes  of data every day. machines and AI-enabled systems that are able to handle this big data. The information regarding the AADHAR Cards of Indian citizens can be an  example of big data . The posts that we like, view, share, or comment on Facebook are also an example of big data. AI has enabled programs to analyze trends in these data and act accordingly . 6

7. Reasons behind why learn AI: Improved disaster management -Many a time, the victims of disasters record videos and share them on social media platforms, like Facebook and Twitter . These platforms have AI-enabled programs in them, which serve as a carrier in spreading the news about these disasters. Benefit of the society- Farmlogs  are software that simplifies the work of farmers by providing them information about the weather, fields, and soil . It is also helping them track irregular plant growth. This is helping them in achieving better profits. Governments are implementing AI in their smart city applications , which is helping them in improving environmental planning, crime prevention, and better resource managemen t . 7

8. Reasons behind why learn AI: AI improvises user experience- AI is not a technology that requires a separate app or device. It is adding intelligence to the products we are using regularly in our lives. A combination of different types of AI technologies like  chatbots , automation, virtual assistants like Google assistant is helping improve user experience by adding multiple useful features to a previously existing product. Siri , the voice assistant that Apple provides specifically for iPhone and iPad users 8

9. Define Intelligence Artificial Intelligence Agent Rationality Logical reasoning 9

10. Define Intelligence: Intelligence is the ability to think, learn and act according to a situation and the environment It is a process of applying knowledge . It can also be defined as the ability to adapt to the changes in the environment . Artificial Intelligence: Artificial Intelligence is the study of making computers as act intelligently like humans . It is the capability of a system to perform the functions similar to a human . Agent : An agent is something that acts. The word ‘ agent’ came from the Latin word “ agree ”, which means, to do . An agent acts on behalf of a person . It is an entity that acts in response to the environmental issues . Rationality : Rationality   means doing the right thing , given what it knows . A rational approach involves a combination of mathematics and engineering Logical reasoning : It is the way of thinking and taking decisions derived from the conclusions and inferences. 10

11. What do you understand by Artificial Intelligence? Artificial intelligence is computer science technology that emphasizes creating intelligent machine that can mimic human behavior "Artificial" and "Intelligence," which means the " man-made thinking ability.“ Do not need to pre-program the machine to perform a task ; instead, create a machine with the programmed algorithms, and it can work on its own. 11

12. Views of AI fall into 4 categories which indicates 13

13. An apple is a fruit.   All fruit is good.   Therefore apples are good. All men are human; all humans are mortal; therefore all men are mortal". 

14. Example : Play chess. In this context, a rational agent is one that makes moves to maximize its chances of winning the game

15. Philosophy Philosophy is the very basic foundation of Al. One important aspect of artificial intelligence is the study of the underlying nature of reality, existence, and knowledge as they relate to addressing a particular problem.. Philosophy defines that how can the formal rules be used to draw valid conclusions. With out philosophy it is difficult to answer the following questions. In what way does a physical brain give rise to mind? Where does the knowledge come from? How does the knowledge lead to action?

16. Mathematics and statistics Al required Formal Logic and Probability for planning and learning. Computation required for analyzing relation and implementation . Knowledge in Formal Representation are most required for writing actions for agents. In Al,the Mathematics & Statistics are most important for Proving theorems, Writing algorithms, Computation, Decidability, Tractability, Modeling uncertainty, Learning from data What are the formal rules to draw valid conclusions? What can be computed? How do we reason with uncertain information?

17. Economics Deals with investing the amount of money and Maximization of utility with minimal investment . While developing an Al product, we should make decisions for When to invest? How to invest? How much to invest? Where to invest? To answer these questions one should have knowledge about Decision Theory, Game Theory, Operation Research etc

18. Neuroscience Neuroscience is the study of the nervous system particularly the human brain. Human brains are somehow different, when compared to other creatures, man has the largest brain in proportion to his size. Since neurons, or nerve cells make up the majority of the brain, understanding a single neuron can provide information about thinking, acting, and brain consciousness. How do brains process information?

19. Neuroscience Cont …. Neurons, also known as nerve cells, send and receive signals from brain. Specialized projections called axons allow neurons to transmit electrical and chemical signals to other cells. Neurons can also receive these signals via root like extensions known as dendrites. Synapses connect neurons in the brain to neurons in the rest of the body and from those neurons to the muscles

20. Psychology/Cognitive Science The scientific method to the study of human vision Problem-solving abilities: how can people make decisions in complex situations? What are people's actions in unexpected circumstances? Perceive: How do you look around you to solve problems? Process cognitive information to represent knowledge. How do humans and animals think and act?

21. Computer Science & Engineering Important areas of computer science include algorithms, programming languages, logic and inference theory, and software system development. Modern programming tools, operating systems, and programming languages were provided by the software branch of computer science. Al has founded many ideas in modern and mainstream computer science including Time sharing, Interactive Interpreters, Personal computers with windows, rapid development environments, the linked-list data type, automatic storage management key concepts of symbolic, functional, declarative and object­ oriented programming Every 100 days, the amount of CPU power used to train the best machine learning applications doubles. The Super computers and quantum computers can solve very complicated Al problems Computer hardware gradually changed for Al applications, such as the graphics processing unit (GPU), tensor processing unit (TPU),and wafer scale engine (WSE) How can we build fast and efficient computer?

22. Control theory Control theory helps the system to analyze, define, debug and fix errors by itself. Developing self-controlling machine, self-regulating feedback control systems and the submarine are some examples of control theory The basis of Algebra is calculus, matrix algebra are the tool of control theory methods that apply to systems that may be described by fixed sets of continuous variables.– to build robot Knowledge representation, grammars, computational linguistics or natural language processing ( N LP) are significant to developing Al applications. Agent programming uses the language, vision, and symbolic planning of computation and logical inference as its instruments. How can artifacts(model-output created by training process) operate under their own control?

23. Linguistics Speech recognition is a technology which enables a machine to understand the spoken language and translate into a machine­ readable format. It is a way to talk with a computer and on the basis of that command, a computer can perform a specific task. It includes Speech to Text, Text to Speech. How does language relate to thought?

24. Economics Deals with investing the amount of money and Maximization of utility with minimal investment . While developing an Al product, we should make decisions for When to invest? How to invest? How much to invest? Where to invest? To answer these questions one should have knowledge about Decision Theory, Game Theory, Operation Research etc