code | CS468 |

credit_hours | 3 |

title | Advanced Artificial Intelligence |

arbic title | |

prequisites | CS366 |

credit hours | 3 |

Describtion/Outcomes | The course introduces the students with a number of modern meta-heuristic techniques taken from the area of natural computation for solving hard optimization problems. The student will be encouraged to solve real world optimization problems using the learnt techniques and to do a guided research on methodological issues of the techniques. |

arabic Describtion/Outcomes | |

objectives | Upon completion of this course, students should be able to:rn rn1. Learn the basic concepts of non-Symbolic AI (Neural Networks and Statistical learning). rn2. Design intelligent systems that can adapt to both uncertainties and changes in their environments. rn3. Understand AI as the design of agents rn4. Apply linear programming refresher, uninformed search, constraint satisfaction problems and algorithms, informed search, heuristics, upper and lower bounding techniques, mixed integer programming, and iterative refinement search. rn |

arabic objectives | |

ref. books | 1. Tom Mitchell, Machine Learning, McGraw-Hill, 1997. rn2. Christopher M. Bishop, Neural Networks for Pattern Recognition, Oxford, 1995. |

arabic ref. books | |

textbook | Russell S. and Norvig P., Artificial Intelligence: A modern Approach, Prentice-Hall, 3rd Edition, 2010. |

arabic textbook | |

objective set | combined |

content set | bullets |