Introduction To Artificial Intelligence - PowerPoint PPT Presentation

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Introduction To Artificial Intelligence

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  1. Introduction To Artificial Intelligence CSC 415-515

  2. What Is (Artificial) Intelligence? • What is intelligence? • The ability tolearn or understand from experience • The ability to acquire and retain knowledge • The ability to respond quickly and successfully to a new situation • The ability to use reason to solve problems CSC 415, Introduction to AI

  3. What Is Artificial Intelligence? • If intelligence is learning, understanding, retaining, responding, and using reason then what is AI? • Is mimicking such phenomena using a machine an expression of artificial intelligence? CSC 415, Introduction to AI

  4. The Turing Test • Place both a human and a machine mimicking human responses outside the field of direct observation and use an unbiased interface to interrogate them. If the responses are distinguishable, the machine is not displaying intelligence. CSC 415, Introduction to AI

  5. Two Foci of AI • Symbol processing • An early thrust of AI research • Stereotyped by expert systems, knowledge bases, and inference engines • Connectionist processing • Typified by emergent computation • Often leads to representations possessing large degrees of parallelism CSC 415, Introduction to AI

  6. Sensor Systems Response Planner Effector Systems An AI Processing Paradigm Input Stimulus Output Response CSC 415, Introduction to AI

  7. Some Key Contributors: A Note on Origins • McCulloch and Pitts (perceptrons) • Turing, von Neumann, Shannon, and McCarthy • Rosenblatt (perceptron learning) • Minsky and Papert • Widrow and Hoff (Adaline) • Zadeh (fuzzy logic) • Werbos, Rumelhart, McClelland, Hinton, Parker, Le Cun • Grossberg, Hopfield • Holland, Goldberg, De Jong, Koza CSC 415, Introduction to AI

  8. What Will We Study? Algorithms and Representation • Sensor systems • Primarily one- and two-dimensional signal sources such as sounds, image data, sunspot counts, or values in a chaotic time series • Other sensor data representation such as ensemble codes and transforms • Response planning • Motion planning—TSP, resource allocation, scheduling • Search strategies—Swarms, GAs, Neural networks • Effector systems • Robot action control CSC 415, Introduction to AI

  9. Robot Demos • Simple line following • Find-and-grab • Robot tag • Robot-to-robot communication (basis for cooperation) • Multi-sensor processing • Two sensor, line following CSC 415, Introduction to AI