Plug IT in 5: Intelligent systems. In this chapter, the learning objectives are: Explain the potential value and the potential limitations of artificial intelligence; provide examples of the benefits, applications, and limitations of expert systems; provide examples of the use of neural networks;. | PLUG IT IN FIVE Intelligent Systems OUTLINE Introduction to Intelligent Systems Expert Systems Neural Networks Fuzzy Logic Genetic Algorithms Intelligent Agents LEARNING OBJECTIVES Explain the potential value and the potential limitations of artificial intelligence Provide examples of the benefits, applications, and limitations of expert systems Provide examples of the use of neural networks Provide examples of the use of fuzzy logic Describe the situations in which genetic algorithms would be most useful Describe the use case for several major types of intelligent agents Introduction to Intelligent Systems Intelligent systems Artificial intelligence (AI) Expert Systems Expertise Expert systems (ESs) Expertise Transfer from Human to Computer Knowledge acquisition Knowledge representation Knowledge inferencing Knowledge transfer The Components of Expert Systems Knowledge base Inference engine User interface Blackboard Explanation subsystem Genetic Algorithms Genetic algorithms have three functional characteristics: • Selection • Crossover: • Mutation: Intelligent Agents Information Agents Monitoring-and-Surveillance Agents User Agents | PLUG IT IN FIVE Intelligent Systems OUTLINE Introduction to Intelligent Systems Expert Systems Neural Networks Fuzzy Logic Genetic Algorithms Intelligent Agents LEARNING OBJECTIVES Explain the potential value and the potential limitations of artificial intelligence Provide examples of the benefits, applications, and limitations of expert systems Provide examples of the use of neural networks Provide examples of the use of fuzzy logic Describe the situations in which genetic algorithms would be most useful Describe the use case for several major types of intelligent agents Introduction to Intelligent Systems Intelligent systems Artificial intelligence (AI) Expert Systems Expertise Expert systems (ESs) Expertise Transfer from Human to Computer Knowledge acquisition Knowledge representation Knowledge inferencing Knowledge transfer The Components of Expert Systems Knowledge base Inference engine User interface Blackboard Explanation subsystem Genetic Algorithms Genetic algorithms have three functional characteristics: • Selection • Crossover: • Mutation: Intelligent Agents Information Agents Monitoring-and-Surveillance Agents User Agents | PLUG IT IN FIVE Intelligent Systems OUTLINE Introduction to Intelligent Systems Expert Systems Neural Networks Fuzzy Logic Genetic Algorithms Intelligent Agents LEARNING OBJECTIVES Explain the potential value and the potential limitations of artificial intelligence Provide examples of the benefits, applications, and limitations of expert systems Provide examples of the use of neural networks Provide examples of the use of fuzzy logic Describe the situations in which genetic algorithms would be most useful Describe the use case for several major types of intelligent agents Introduction to Intelligent Systems Intelligent systems Artificial intelligence (AI) Expert Systems Expertise Expert systems (ESs) Expertise Transfer from Human to Computer Knowledge acquisition Knowledge representation Knowledge inferencing Knowledge transfer The Components of Expert Systems Knowledge base Inference engine User interface Blackboard Explanation subsystem .
