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CSBP301: Artificial Intelligence

Description:Principles and methods for knowledge representation, reasoning, learning, problem solving, planning, heuristic search, natural language processing, speech recogition; LISP, PROLOG, or expert system programming languages. Pre-requisite: ITBP320
Credit Hours.:3
Text Book: Introducing Artificial Intelligence, Henry Brighton, Howard Selina, (1st edition), 2003, ISBN-13: 978-1840468410
Coordinator: Jose Lopez Berengueres
Topics Outline:
  1. History of AI.
  2. Introduction to Agents.
  3. Overview of search algorithms. Heuristics. Deep-first breath. Hill-climbing. Ant colony.
  4. Implementation techniques in python/java. TSP, sudoku solver, prissioner's dilema, iRoomba as an agent.
  5. Overview of Speech Processing. The human tract model.
  6. Computer Vision. Introduction to morphological operators: opening and closing only. Implement face detection - tracking with OpenCV MS VC++ / Sara robot. Implement a bean sorter/counter. Use of opening as a noise reduction filter.
  7. AI Industry Applications by case study.
  1. Explain the main aspects of the problem of Intelligence
  2. Design and write programs for simple agents and decision-making systems
  3. Explain the principles and methods of pattern recognition
  4. Explain the main problems and methods of computer vision, natural language processing, and intelligent robotics
  5. Evaluate real-world pattern recognition, computer vision, natural language and robotics systems
  6. Synthesize a simple AI system.
Mapping of Topics Outline to Outcomes
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Pre-requisiteITBP319: Data Structures
Co-requisite CSBP331: Artificial Intelligence and Robotics Lab
Volume of the Course that Contributes to CIT Students Outcomes(SOs)
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a b c d e f g h i j k l m n
13% 23% 9% 2% 2% 6%2% 2% 2% 13% 9% 4% 9% 4%
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