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Seminar on Artificial Intelligence

Seminar on Artificial Intelligence

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Seminar on Artificial Intelligence

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  1. Seminar on Artificial Intelligence

  2. ARTIFICIAL INTELLIGENCE Artificial intelligence is a branch of computer science concerned with the study and creation of computer systems that exhibit some form of intelligence.

  3. Form of intelligence means :- • Systems that can reason and draw useful conclusions about the world around us. • Systems that can understand a natural language or perceive and comprehend a visual scene. • Systems that perform other type of feats that require human types of intelligence. • Systems that learn new concepts and tasks. more and more…..

  4. AI is not only INTELLIGENCE but also related with the terms KNOWLEDGE, REASONING, SEARCHING, THOUGHT, COGNITION, LEARNING and number of computer related terms.

  5. The meaning of AI is found accuratelyin the areas of study about • ROBOTICS • MEMORY ORGANISATION • KNOWLEDGE REPRESENTION • STORAGE AND RECALL • LEARNING MODELS • INFERENCE TECHNIQUES • COMMON SENSE RESONING • DECISION MAKING • NATURAL LANGUAGE • PATTERN RECOGNITION • MACHINE VISION • SEARCH AND MATCHING

  6. History:- Involvement of AI into computer system is during 1940-1950. In 1970, Japanese were the 1st to demonstrate their commitment. They launched a very ambitious program in AI research and development known as “Fifth Generation”. It was officially announced in October 1981. Then after the British initiated a plan called “Alvay Project”. The European common market countries have jointly initiated a separate co-operative plan named the “ESPRIT PROGRAM”.

  7. AI RESEARCH:- Some organizations took steps forward in AI research. They are:- • The consortium of private companies, “MCC” (Microelectronics and Computer technology Corporation) developed the advanced technology like “VLSI”. • It’s headquarter is in “Austin” and “Texas”. • The “Department of Defence Advanced Research Project Agency”. It was worked on some significant programs.

  8. Different tasks or task domain of AI:- • Formal Task: • Mundane Task: • Expert Task:

  9. Aim of using AI:- AI is a technique that exploits knowledge and this knowledge 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. It can reflects changes in the world. It can be used in many situations even if it is not totally accurate or complete.

  10. Applications of AI:- • Solving Problems: • Production System: • Expert System: • Knowledge Representation: • Computer Perception: • Searching and Matching: • Natural language Parsing:

  11. Conclusion:- Father of Artificial Intelligence Mr. Marvin Minsky gifted this important and useful task towards the human being, through this computer and was remembered for always for his invention.

  12. Games: Chess Backgammon Checkers Go Mathematic: Geometry Logic Integral Calculus Proving properties

  13. Engineering : Design Fault Finding Manufacturing Planning • Scientific Analysis: • Medical Diagnosis: • Financial Analysis:

  14. Perception: Vision Speech Natural Language: Understanding Generation Translation Common Sense Reasoning: Robot Control:

  15. Development of an Autonomous Land Vehicle (ALV) :A driverless military vehicle. • Development of a Pilot’s Association :An expert system which provides assistance to a fighter pilot. • The strategic computing program : An AI based military super computer project. • DEDALUS : An automatic programming system • LIFER : An intelligent “tool”. • NOAH : A planning system for Robots. • PROSPECTOR : An expert system that acts as a geologist’s assistant in mineral exploration.

  16. Solving problems:- One of the great application of AI is it’s problem solving procedure. AI solves different problems through these set of rules- • Define the problem preciously. • Analyze the problem. • Isolate and represent the task knowledge that is necessary to solve the problem. • Choose the best problem solving technique and apply it to the particular problem.

  17. Production System:- • A set of rules having a left side that determines the applicability of the rule and a right side describes the operation to be performed. • One or more databases/knowledge that contain the information which is appropriate for the particular task. Some part of the database are permanent. Others are meant for solving the particular task. • A control strategy that specifies the order in which the rules will be compared and away of resolving the conflicts that arise when several rules match at once. • A rule applier, who applies that rule over that particular problem. application of PS:

  18. Applications of Production System:- • The design of VLSI systems. • Location of faults in computer and communication. • Different types of medical diagnosis. • Diagnosis of software development project. • Numerous applications related to space planning and exploration . • Teaching students specified task. • Identification of chemical compounds structure. • Fore casting crop damage. PS Language:

  19. Production system languages:- • OPS5 : BROWNSTON IN 1985 • ACT* : ANDERSON IN 1983 • SOAR : LAIRD IN 1987 (general problem solving architecture)

  20. Expert Systems:- • It is a set of program that manipulate encoded knowledge to solve problems. • Expert systems are knowledge rather then data. • It can explain how particular conclusion is reached and why requested information is needed during consultation. • It uses symbolic representation for knowledge and perform their inference through symbolic computations.

  21. Knowledge Representation:- • Knowledge:It is the collection of facts, inference rules which is applied on different task. • Procedural Knowledge. • Declarative Knowledge. • Schemes / Techniques : • Logical. • Semantic. • Conceptual. • Scripts. • Frames. • Production rules. Example :

  22. Example of representing Knowledge:- Has Eats Teeth Mammal Food Rodent Rabbit • Rabbit is rodent. • Rodent is mammal. • Mammal eats food and has teeth. Then this can be represented as –

  23. Computer Perception:- • Vision recognition: Visual perception generally refers to the construction of knowledge to understand and interpret 3-dimensional objects from the sense that human and machine perceives through their visual Image are two dimensional • Speech recognition: Speech is the most expedient and natural form of communication. It has advantages like- • Program can communicate directly with the machine. • The speed of the interchange of information between the user and the system is faster. • Human communication often involves spoken language. So that it is easier for us to communicate with the systems. Speech rules:

  24. Speech acts:- There are several categories of speech acts: • Representative: those that state a proposition. • Directive : that request or command • Co missives : that promise or threaten • Ex pressives : that thanks or apologize • Declarative : that actually change the state of world.

  25. Searching and Matching There are several algorithms involved. These are – Best First Search. Depth First Search. Breadth First Search. Application of these searching techniques are- Cannibals Missionaries Problem. Water Jug Problem. Hill Climbing Method. Tic Tac Toe. 8-puzzle Game (A* Algorithm). etc..

  26. Natural Language Processing:- It is required that a program transforms sentence into data structure, by the help of a parser, which convey the original meaning of that sentence. Two types of parsing techniques are there : • Top-down Approach • Bottom-up Approach

  27. Top-down Approach:- Back For instance: The Handsome Boy Loves A Nice Girl. Ans: S NP VP ART NP V NP ADJ. N ART NP ADJ. N THE HANDSOME BOY LOVES A NICE GIRL

  28. Bottom-up Approach: Back For instance: The Handsome Boy Loves A Nice Girl. Ans. The Handsome Boy Loves A Nice Girl. ART ADJ. N V ART ADJ N NP NP NP NP VP S