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Artificial intelligence priti sajja spuniversity



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  • 1. Artificial Intelligence Priti Srinivas Sajja Associate Professor Department of Computer Science Sardar Patel University Visit priti for detail Created By Priti Srinivas Sajja 1
  • 2. Artificial IntelligenceIntroductionIntroduction Natural intelligenceAI Tests  Responds to situations flexibly.Applications  Makes sense of ambiguous or erroneous messages.  Assigns relative importance to elements of aData Pyramid situation.Knowledge  Finds similarities even though the situations mightBased Systems be different.Pros and Cons  Draws distinctions between situations even thoughBio-inspired there may be many similarities between them.ExampleAcknowledgement 2 Created By Priti Srinivas Sajja
  • 3. Artificial IntelligenceIntroductionIntroduction Artificial intelligenceAI TestsApplicationsData PyramidKnowledgeBased SystemsPros and ConsBio-inspiredExampleAcknowledgement 3 Created By Priti Srinivas Sajja
  • 4. Artificial IntelligenceIntroductionIntroduction Artificial intelligenceAI Tests human thought processApplications heuristic methods where people are betterData Pyramid non-algorithmicKnowledgeBased Systems characteristics we associate knowledge using symbolsPros and Cons with intelligenceBio-inspired Constituents of artificial intelligenceExampleAcknowledgement 4 Created By Priti Srinivas Sajja
  • 5. Artificial IntelligenceIntroductionIntroduction Artificial intelligenceAI TestsApplications Acceptable ExtremeData Pyramid solution in solution, either acceptable best or worstKnowledge time taking  (infinite) timeBased SystemsPros and Cons time Nature of AI solutionsBio-inspiredExampleAcknowledgement 5 Created By Priti Srinivas Sajja
  • 6. Artificial IntelligenceIntroduction Testing Intelligence Turing test will fail to test for intelligence in two circumstances;AI TestsAI Tests 1. A machine may well be Can you tell intelligent withoutApplications me what is 222222*67344 ? being able to chat exactly like a human; and;Data Pyramid Why Sir? 2. The test fails to captureKnowledge the general properties ofBased Systems intelligence, such as the ability to solve difficultPros and Cons The Boss could not judge who was replying, problems or come up with thus the machine is as intelligent as the original insights. If a secretary.Bio-inspired machine can solve a difficult problem that The Turing testExample no person could solve, it would, in principle, failAcknowledgement the test. 6 Created By Priti Srinivas Sajja
  • 7. Artificial Intelligence Can you find any test to check the given system is intelligent or not?Introduction Walks,AI TestsAI Tests Makes and perceives, tests, understands joke smells, and feels likeApplications human Reacts differentlyData Pyramid Solves yourKnowledge problem If it talksBased Systems like humanPros and ConsBio-inspired Translates, conceptually form a test summarizes,Example and use it in different situation and learns before accepting it.Acknowledgement 7 Created By Priti Srinivas Sajja
  • 8. Artificial Intelligence Rich & Knight (1991) classified and described the different areas thatIntroduction Artificial Intelligence techniques have been applied to as follows:AI TestsApplicationsApplications Mundane Tasks Expert Tasks • Perception - vision and • Engineering - design, faultData Pyramid speech finding, manufacturing • Natural language planning, etc.Knowledge understanding, generation, • Scientific analysisBased Systems and translation • Medical diagnosis • Commonsense reasoningPros and Cons • Financial analysis • Robot control Formal Tasks • Games - chess,Bio-inspired backgammon, checkers, etc. • Mathematics- geometry,Example logic, integral calculus, theorem proving, etc.Acknowledgement 8 Created By Priti Srinivas Sajja
  • 9. Artificial IntelligenceIntroduction ISAI Tests Strategy makers apply morals, WBS Wisdom (experience) principles, and experience to generateApplications policies Higher management generates Knowledge (synthesis) KBS knowledge by synthesizingDataPyramidData Pyramid information Middle management uses reports/info. DSS, MIS Information (analysis)Knowledge generated though analysis and acts accordinglyBased Systems TPS Data (processing of raw observations ) Basic transactions by operationalPros and Cons staff using data processingBio-inspired Volume Sophistication and complexityExample Data pyramidAcknowledgement 9 Created By Priti Srinivas Sajja
  • 10. Artificial IntelligenceIntroduction Knowledge Inference base engine Explanation Self-AI Tests and learning reasoning User interfaceApplicationsData PyramidKnowledgeKnowledge General structure of KBSBased systemsBased SystemsPros and Cons According to the classifications by Tuthhill & Levy (1991), five main types of KBS exists:  Expert systemsBio-inspired  Linked Systems  CASE based SystemsExample  Intelligent Tutoring Systems  Intelligent User Interface for DatabaseAcknowledgement 10 Created By Priti Srinivas Sajja
  • 11. Artificial IntelligenceIntroduction Knowledge Sources and TypesAI TestsApplicationsData PyramidKnowledgeKnowledgeBased systemsBased SystemsPros and ConsBio-inspiredExampleAcknowledgement 11 Created By Priti Srinivas Sajja
  • 12. Artificial IntelligenceIntroduction Knowledge RepresentationAI TestsApplicationsData PyramidKnowledgeKnowledgeBased systemsBased SystemsPros and ConsBio-inspiredExampleAcknowledgement 12 Created By Priti Srinivas Sajja
  • 13. Artificial IntelligenceIntroduction  Intelligence, explanation and reasoning  Partial self learning, uncertainty handlingAI Tests  Documentation of knowledgeApplications  Proactive problem solving  Cost effectivenessData PyramidKnowledgeBased Systems  Nature of knowledge  Large volume of knowledgePros and ConsPros and Cons  Knowledge acquisition techniquesBio-inspired  Little support to engineer AI based systems  Shelf life of knowledge and systemExample  Development EffortAcknowledgement 13 Created By Priti Srinivas Sajja
  • 14. Artificial IntelligenceIntroduction Bio-Inspired ComputingAI Tests  New approaches to AI  Taking inspiration form nature and biological systemsApplications  Includes models such as  Artificial Neural Network (ANN),Data Pyramid  Genetic Algorithm(GA),Knowledge  Swarm Intelligence(SI), etc.Based Systems  Nature has virtues of self learning, evolution,Pros and Cons emergence and immunity  The objective of bio-inspired models and techniques toBio-inspiredBio-inspired take inspiration from Mother Nature and solve problems in more effective and intelligent wayExampleAcknowledgement 14 Created By Priti Srinivas Sajja
  • 15. Artificial IntelligenceIntroduction Artificial Neural Network (ANN)AI Tests  An artificial neural network (ANN) is connectionist model of programming using computers.Applications  An ANN attempts to give computers humanlike abilities by mimicking the human brain’s functionality.Data Pyramid  The human brain consists of a network of more than a hundred billions interconnected neurons working in a parallel fashion.KnowledgeBased Systems W1 X1Pros and Cons X2 W2 XiWi y … ….Bio-inspiredBio-inspired W n XnExample A biological neuron An artificial neuronAcknowledgement 15 Created By Priti Srinivas Sajja
  • 16. Artificial IntelligenceIntroductionAI TestsApplicationsData Pyramid Input layer Hidden layersKnowledge X1 W12 Output layerBased Systems X2 O0Pros and Cons X3 . . . O1 . . . . . . . . ….Bio-inspiredBio-inspired . . . . Om .Example Xn W1h A multilayer perceptronAcknowledgement 16 Created By Priti Srinivas Sajja
  • 17. Artificial IntelligenceIntroduction Genetic Algorithms (GA) • It mimics Nature’s evolutionary approachAI Tests • The algorithm is based on the process of natural selection— Charles Darwin’s “survival of the fittest.”Applications • GAs can be used in problem solving, function optimizing, machine learning, and in innovative systems.Data Pyramid Start with initial population by randomly selected Initial population IndividualsKnowledge ModifyBased Systems with Selection Crossover Mutation operationsPros and Cons Evaluate fitness of new Evaluating new individuals through fitness functionBio-inspiredBio-inspired individuals Update population with better individuals and Modify the populationExample repeat Genetic cycleAcknowledgement 17 Created By Priti Srinivas Sajja
  • 18. Artificial IntelligenceIntroduction Swarm IntelligenceAI Tests  Inspired by the collective behavior of social insect colonies and other animal societiesApplications  Ant colony, fish school, bird flocking and honey comb are the examplesData PyramidKnowledgeBased SystemsPros and ConsBio-inspiredBio-inspiredExampleAcknowledgement 18 Created By Priti Srinivas Sajja
  • 19. Artificial IntelligenceIntroduction Some more examples ….AI TestsApplicationsData PyramidKnowledgeBased SystemsPros and ConsBio-inspiredBio-inspiredExampleAcknowledgement 19 Created By Priti Srinivas Sajja
  • 20. Artificial IntelligenceIntroductionAI Tests Implicit and self learning Fuzzy Interface by ANNApplicationsData PyramidKnowledge UnderlyingBased Systems Users choice Fuzzy interface ANN and needs Linguistic Fuzzy rule base Crisp P 1Pros and Cons P fuzzy and membership Normalized 2 P 3 P interface functions values 4 RulebaseBio-inspired Decision support Decision support Structure of proposed systemExampleAcknowledgement 20 Created By Priti Srinivas Sajja
  • 21. Artificial IntelligenceIntroductionAI TestsApplicationsData PyramidKnowledgeBased SystemsPros and ConsBio-inspiredExampleExampleAcknowledgement 21 Created By Priti Srinivas Sajja
  • 22. Artificial IntelligenceIntroduction References  llustrationsOf.comAI Tests    scenicreflections.comApplications   business2press.comData Pyramid   Knowledge-based systems, Akerkar RA and Priti Srinivas Sajja, Jones & Bartlett Publishers, Sudbury, MA, USA (2009)KnowledgeBased SystemsPros and ConsBio-inspiredExampleAcknowledgement 22 Created By Priti Srinivas Sajja