1. Introduction to Artificial Intelligence by Tanu Dixit CS-3 rd year

2. What is INTELLIGENCE??? The ability to comprehend, understand and get profit from experience. 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.

3. Artificial intelligence may be defined in a number of ways  AI refers to an algorithm or set of algorithms that can make decisions in a logical way.  AI is the use of programs to enable machines to perform tasks which humans perform using their intelligence.  AI is the process of inducing intelligence into the machines, artificially/externally.  The branch of computer science that deal with writing computer programs that can solve problems creatively

4. What type of reasoning is connected with Artificial Intelligence??? The AI routine for a bad guy in a game might let him figure out how to find you. Another use of AI is to have a maze or puzzle solved automatically. Artificial Intelligence (AI) is used in games for everything from making a computer opponent behave believably like a human opponent to having automated units perform tasks in a realistic manner.

5.  Learn from experience.  Apply knowledge acquired from experience.  Handle complex situations.  Solve problems when important information is missing.  React quickly and correctly to a new situation.  Understand visual images.  Process and manipulate symbols.  Be creative and imaginative.  Use heuristics. Intelligent Behavior

6. GOALS Among the traits that researchers hope machines will eventually exhibit are:  Reasoning  Knowledge  Planning  Learning  Communication  Perception General Intelligence (or, Strong AI) is the ultimate long-term goal of researchers, although it has yet to be achieved.

7. REQUIREMENTS For a potential AI unit to be considered “alive” or “intelligent” it would have to exceed its original programming.  The AI questioning its original programming without provocation. AI was programmed to go “beep” every minute and then left alone to do so, eventually it would wonder if it was necessary to beep every minute.  The AI being able to solve problems it was not originally programmed to solve. This requirement shows an ability to apply deductive reasoning without connections that have been specifically laid beforehand. It further requires the AI to draw upon all of its “knowledge” and “skills” This idea further extends to the AI making connections that it was not specifically given; applying methods to situations where the methods weren’t originally intended to be applied, getting results, and either discarding the results as nonsensical or realizing that they are valid.

8. The philosophy of artificial intelligence “Can machines think?” In the years since it was proposed, several answers have been given:  Newell and Simon’s physical symbol system hypothesis: A physical symbol system has the necessary and sufficient means of general intelligent action. Claims the essence of intelligence is symbol manipulation.  Hubert Dreyfus argued that, on the contrary, human expertise depends on unconscious instinct rather than conscious symbol manipulation.  Turing’s “polite convention”: If a machine acts as intelligently as a human being, then it is as intelligent as a human being. This ‘convention’ forms the basis of the Turing test.

9. Problems of Artificial Intelligence Deduction, Reasoning, and Problem Solving Deduction, Reasoning, and Problem Solving Early AI researchers developed algorithms that could imitate the process of conscious, step-by-step reasoning that human beings use when they solve puzzles or make logical deductions. Early AI researchers developed algorithms that could imitate the process of conscious, step-by-step reasoning that human beings use when they solve puzzles or make logical deductions. By the 80s and 90s, AI research had also developed successful methods for dealing with uncertain or incomplete information by using concepts from probability and economics. By the 80s and 90s, AI research had also developed successful methods for dealing with uncertain or incomplete information by using concepts from probability and economics.

10. Knowledge Representation Knowledge Representation Most problems machines are expected to solve require extensive knowledge about the world. Some things that AI needs to have information on is: Most problems machines are expected to solve require extensive knowledge about the world. Some things that AI needs to have information on is: Objects and their Properties Objects and their Properties Categories and Relations between objects Categories and Relations between objects Situations and Events Situations and Events States States Time Time Cause and effect Cause and effect Knowledge about knowledge (what we know about what other people know) Knowledge about knowledge (what we know about what other people know)Problems Default reasoning: Default reasoning: Qualification problem:. Qualification problem:. Unconscious knowledge: Unconscious knowledge: Common sense knowledge: Common sense knowledge:

11. Planning: Planning: Intelligent agents must be able to set goals and achieve them. Intelligent agents must be able to set goals and achieve them. They need a way to visualize the future. They must have a representation of the state of the world and be able to make predictions about how their actions will change it. They need a way to visualize the future. They must have a representation of the state of the world and be able to make predictions about how their actions will change it. They must also attempt to determine the utility or "value" of the choices available to it. They must also attempt to determine the utility or "value" of the choices available to it. Problem: Problem: Often, the agent assumes that it is the only thing acting on the world and it can be certain what the consequences of it's actions may be. However, if this is not true, it must periodically check if the world matches its predictions and it must change its plan as this becomes necessary, requiring the agent to reason under uncertainty. Often, the agent assumes that it is the only thing acting on the world and it can be certain what the consequences of it's actions may be. However, if this is not true, it must periodically check if the world matches its predictions and it must change its plan as this becomes necessary, requiring the agent to reason under uncertainty.

12. Major Branches of AI Perceptive system Perceptive system A system that approximates the way a human sees, hears, and feels objects A system that approximates the way a human sees, hears, and feels objects Vision system Vision system Capture, store, and manipulate visual images and pictures Capture, store, and manipulate visual images and pictures Robotics Robotics Mechanical and computer devices that perform tedious tasks with high precision Mechanical and computer devices that perform tedious tasks with high precision Expert system Expert system Stores knowledge and makes inferences Stores knowledge and makes inferences

13. Learning system Learning system Computer changes how it functions or reacts to situations based on feedback Computer changes how it functions or reacts to situations based on feedback Natural language processing Natural language processing Computers understand and react to statements and commands made in a “natural” language, such as English Computers understand and react to statements and commands made in a “natural” language, such as English

14. Artificial intelligence

15. Capabilities of Expert Systems Strategic goal setting Decision making Planning Design Quality control and monitoring Diagnosis

16. When to Use an Expert System Provide a high potential payoff or significantly reduced downside risk. Provide a high potential payoff or significantly reduced downside risk. Capture and preserve irreplaceable human expertise. Capture and preserve irreplaceable human expertise. Provide expertise needed at a number of locations at the same time or in a hostile environment that is dangerous to human health. Provide expertise needed at a number of locations at the same time or in a hostile environment that is dangerous to human health.

17. Provide expertise that is expensive or rare. Provide expertise that is expensive or rare. Develop a solution faster than human experts can. Develop a solution faster than human experts can. Provide expertise needed for training and development to share the wisdom of human experts with a large number of people. Provide expertise needed for training and development to share the wisdom of human experts with a large number of people.

18. Inference engine Explanation facility Knowledge base acquisition facility User interface Knowledge base Experts User

19. Components of an Expert System Knowledge base Knowledge base Inference engine Inference engine Rule Rule Fuzzy logic Fuzzy logic Backward chaining Backward chaining Forward chaining Forward chaining

20. Today: The Difference Between Us and Them

22. ADVANTAGES (Factual Changes)  Smarter artificial intelligence promises to replace human jobs, freeing people for other pursuits by automating manufacturing and transportations.  Self-modifying, self-writing, and learning software relieves programmers of the burdensome task of specifying the whole of a program’s functionality—now we can just create the framework and have the program itself fill in the rest (example: real-time strategy game artificial intelligence run by a neural network that acts based on experience instead of an explicit decision tree).  Self-replicating applications can make deployment easier and less resource-intensive.  AI can see relationships in enormous or diverse bodies of data that a human could not

23. Disadvantages (Risks) Potential for malevolent programs, “cold war” between two countries, unforeseen impacts because it is complex technology, environmental consequences will most likely be minimal. Potential for malevolent programs, “cold war” between two countries, unforeseen impacts because it is complex technology, environmental consequences will most likely be minimal.

24. Self-modifying, when combined with self- replicating, can lead to dangerous, unexpected results, such as a new and frequently mutating computer virus. Self-modifying, when combined with self- replicating, can lead to dangerous, unexpected results, such as a new and frequently mutating computer virus. As computers get faster and more numerous, the possibility of randomly creating an artificial intelligence becomes real. As computers get faster and more numerous, the possibility of randomly creating an artificial intelligence becomes real. Military robots may make it possible for a country to indiscriminately attack less-advanced countries with few, if any, human casualties. Military robots may make it possible for a country to indiscriminately attack less-advanced countries with few, if any, human casualties. Rapid advances in AI could mean massive structural unemployment Rapid advances in AI could mean massive structural unemployment AI utilizing non-transparent learning (i.e. neural networks) is never completely predictable AI utilizing non-transparent learning (i.e. neural networks) is never completely predictable

25. Applications fields of artificial intelligence  Computer science  Finance  Medicine  Heavy industry  Online and telephone customer service  Transportation  Music

26. The Future? Idea of Artificial Intelligence is being replaced by Artificial life, or anything with a form or body. Idea of Artificial Intelligence is being replaced by Artificial life, or anything with a form or body. The consensus among scientists is that a requirement for life is that it has an embodiment in some physical form, but this will change. Programs may not fit this requirement for life yet. The consensus among scientists is that a requirement for life is that it has an embodiment in some physical form, but this will change. Programs may not fit this requirement for life yet.

27. FUTURE PROSPECTS: FUTURE PROSPECTS: Nobody has seen the future and this accounts for the unpredictability in the field of AI, what we feel that the scopes are bright for some strategy based works. Man or the machines? This question will be out of focus since the only thing which creates the difference between the man and the machine will be vaporized. Further when emotions will be transferred a lot of other topics can get light over which the humans have also been not able to think of.

28. Should we start caring yet? Very sophisticated—perhaps even sentient—AI may not be far off; with sufficient computation power (such as that offered by quantum computers) it is possible to “evolve” AI without much programming effort. Very sophisticated—perhaps even sentient—AI may not be far off; with sufficient computation power (such as that offered by quantum computers) it is possible to “evolve” AI without much programming effort. Today, concerns include mutating viruses and the reliability of AI (you don’t want software directing your car into a tree). Today, concerns include mutating viruses and the reliability of AI (you don’t want software directing your car into a tree).

29. What should happen When programs that appear to demonstrate sentience appear (intelligence and awareness), a panel of scientists could be assembled to determine if a particular program is sentient or not. When programs that appear to demonstrate sentience appear (intelligence and awareness), a panel of scientists could be assembled to determine if a particular program is sentient or not. If sentient, it will be given rights, so, in general, companies will try to avoid developing sentient AI since they would not be able to indiscriminately exploit it. If sentient, it will be given rights, so, in general, companies will try to avoid developing sentient AI since they would not be able to indiscriminately exploit it. Software companies should be made legally responsible for failings of software that result in damage to third parties despite good-faith attempts at control by the user. Software companies should be made legally responsible for failings of software that result in damage to third parties despite good-faith attempts at control by the user. AI and robotics have the potentially to truly revolutionize the economy by replacing labor with capital, allowing greater production—it deserves a corresponding share of research funding! AI and robotics have the potentially to truly revolutionize the economy by replacing labor with capital, allowing greater production—it deserves a corresponding share of research funding!

30. Deep Blue Deep Blue was a chess-playing computer developed by IBM. Deep Blue was a chess-playing computer developed by IBM. On May 11 th, 1997, the machine won a six-game match by two wins to one with three draws to Garry Kasparov, the world champion. On May 11 th, 1997, the machine won a six-game match by two wins to one with three draws to Garry Kasparov, the world champion. The system derived its playing strength mainly out of brute force computing power. It was a massively parallel, 30-node, RS/6000, SP-based computer system enhanced with 480 special purpose VLSI chess chips. The system derived its playing strength mainly out of brute force computing power. It was a massively parallel, 30-node, RS/6000, SP-based computer system enhanced with 480 special purpose VLSI chess chips. It was capable of evaluating 200 million positions per second, twice as fast as its earlier version. In June 1997, Deep Blue was the 259th most powerful supercomputer in the world, capable of calculating 11.38 gigaflops. It was capable of evaluating 200 million positions per second, twice as fast as its earlier version. In June 1997, Deep Blue was the 259th most powerful supercomputer in the world, capable of calculating 11.38 gigaflops. A gigaflop is billion floating-point operations per second (FLOPS). A gigaflop is billion floating-point operations per second (FLOPS). 11380000000 operations per second 11380000000 operations per second

31. Deep blue as an instance was able to beat Gary kasporov, a very famous chess player. We must bring to your notice that Deep Blue is a computer which has got some of the powers of reasoning. Chess is a game which requires a lot of reasoning and strategy. And that computer has got that much of brains that fewer chances have occurred that that computer has been beaten up.

32. This must be made clear that AI is just not reasoning. Suppose someday if emotions are poured into the machines, then a lot of other working spaces will be opened. Suppose the humanoids can be sent to crèche for treating those children. The level of technology will be such that those children will not be able to distinguish between humans and robots. Well, when this AI concept will come into existence, the technology will develop humans, instead of humans developing technology. Conclusions