Artificial Intelligence: Difference between revisions

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Artificial intelligence (AI) is intelligence exhibited by machines. In computer science, the field of AI research defines itself as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of success at some goal. Colloquially, the term "artificial intelligence" is applied when a machine mimics "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving"<ref>https://en.wikipedia.org/wiki/Artificial_intelligence</ref>
Artificial intelligence (AI) is intelligence exhibited by machines. In computer science, the field of AI research defines itself as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of success at some goal. Colloquially, the term "artificial intelligence" is applied when a machine mimics "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving"<ref>https://en.wikipedia.org/wiki/Artificial_intelligence</ref>

Latest revision as of 14:46, 31 May 2023

Artificial Intelligence[1]



Artificial intelligence (AI) is intelligence exhibited by machines. In computer science, the field of AI research defines itself as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of success at some goal. Colloquially, the term "artificial intelligence" is applied when a machine mimics "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving"[2]

For now (January 2018), this page is a collection of my notes from my graduate class, which I will build upon and share with my students. The structure of this information is "note-taking, not ready for structured learning by students". 

The big ideas in AI[edit]

  1. Natural Language Processing
  2. Problems in AI
  3. Characteristics of AI agents
  4. Three fundamentals of knowledge-based AI
  5. Four schools of AI
  6. Semantic relationships
  7. Means-Ends Analysis
  8. Problem Reduction
  9. Production System
  10. Frames
  11. Learning by recording cases
  12. Case-based reasoning
  13. Incremental concept learning
  14. Logic
  15. Planning
  16. Primitive action

Standards[edit]

References[edit]