Artificial Intelligence


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Artificial Intelligence

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Artificial Intelligence

  1. 1.  Intelligence is the ability to learn about, learn from, understand, and interact with one’s environment. This general ability consists of a number of specific abilities, which include these specific abilities:  Adaptability to a new environment or to changes in the current environment  Capacity for knowledge and the ability to acquire it  Capacity for reason and abstract thought  Ability to comprehend relationships  Ability to evaluate and judge  Capacity for original and productive thought
  2. 2. WisdomIntelligenceKnowledgeInformation Data
  3. 3.  AI is the study of how to make computers do things which, at the moment, people do better AI is a branch of computer science concerned with teaching computers to think The capability of a device to perform functions that are normally associated with human intelligence, such as reasoning and optimization through experience AI is the branch of computer science concerned with the study and creation of computer systems that exhibits some form of intelligence-  Learn new concepts and tasks  Can reason and draw useful conclusion  Can understand a natural language
  4. 4. AI HI AI, when given the information can be When HI is given the same exact, every time with speed. information, it can not be as exact, and AI are digital is slower. AI uses byte-addressable memory.  HI are analogue  The HI uses content-addressable There is a appealing hardware/software memory distinction obscures in AI  No hardware/software distinction can be made with respect to the brain or mind Processing and memory are performed Processing and memory are performed by the different components. by the same components in the brain AI could do this if it was program to  Human intelligence can forget and lose do so, but this would be counter- productive. information
  5. 5. Mundane Tasks Formal Tasks Perception  Games  Vision  Chess  Speech  Checkers-Go Natural Language  Mathematics  Understanding  Geometry  Generation  Logic  Translation  Integral calculus Commonsense reasoning  Proving properties of programs Robot control
  6. 6. Expert Tasks Engineering  Design  Fault finding  Manufacturing planning Scientific analysis Medical diagnosis Financial analysis
  7. 7.  This assumption was given by Newell and simon. They call this assumption the physical symbol system hypothesis. They define a physical symbol system as follows:- A physical symbol system consists of a set of entities called symbols, which are physical patterns that can occur as components of another type of entity called an expression or symbol structure. A symbol structure is composed of a number of instances (or tokens) of symbols related in some physical way. At any instance of time the system will contain a collection of these symbols structures. Besides these structures ,the system also contains a collection of processes that operate on expressions to produce other expressions: processes of and destruction.
  8. 8.  A physical symbol system is a machine that produces through time an evolving collection of symbol structures. This hypothesis is only a hypothesis. There appears to be no way to prove or disprove it on logical grounds. The only way to determine its truth is by experimentation.
  9. 9.  An AI technique is a method that exploits knowledge that should be represented in such a way that:  The knowledge captures generalization.  It can be understood by people who must provide it.  It can easily be modified to correct errors and to reflect changes in the world and in our world view.  It can be used in a great many situations even if it is not totally accurate or complete.  It can be used to help overcome its own sheer bulk by helping to narrow the range of possibilities that must usually be considered.
  10. 10.  “What is our goal in trying to produce programs that do the intelligent things that people do?”  Are we trying to produce programs that do the tasks the same way people do?  Are we attempting to produce programs that simply do the task in whatever way appears easiest?
  11. 11.  Efforts to build programs that perform tasks the way people do can be divided into two classes:- In first class:-  Programs that attempt to solve problems that do not really fit our definition of an AI task.  They are problems that a computer could easily solve.  Although that easy solution would exploit mechanisms that do not seem to be available to people.
  12. 12.  In second class:-  Programs that attempt to model human performance are those that do things that fall more clearly within our definition of AI tasks.  They do things that are not trivial for the computers.  There are several reasons one might want to model human performance at these sorts of tasks:  To test psychological theories of human performance  To enable computers to understand human reasoning  To enable people to understand computer reasoning  To exploit what knowledge we can glean from people.
  13. 13.  In 1950,Alan Turing proposed the method for determining whether a machine can think. This method is known as Turing test. To conduct this test, we need  2 people  1 machine One person plays the role of the interrogator, who is in a separate room from the computer and the other person. The interrogator can ask questions of either the person or the computer by typing questions and receiving typed responses. The interrogator knows them only as A and B
  14. 14.  The goal of the machine is to fool the interrogator into believing that it is the person. If the machine succeeds at this, then we conclude that the machine can think.