جامعة جرش الاهلية JERASH PRIVATE UNIVERSITY
قسم علوم الحاسوبComputer Science Dept.

Course Title:Artificial Intelligent

Course prerequisite(s) and/or corequisite(s):1001223 / Course code: 1001310
Credit hours: 3 / Course Level: Fourth
Semester/Lecture Time:

Instructor Details

Instructor Name
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e-mail
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Office Hours

Course Description

This course aims to introduce the main concepts of artificial intelligence. This includes types of problems and techniques in Artificial Intelligence. Problem-Solving methods. Major structures used in Artificial Intelligence programs. Study of knowledge representation techniques such as predicate logic, non-monotonic logic, and probabilistic reasoning. Application areas of AI such as game playing, expert systems, natural languages understanding and robotics. Project assignments in one of the AI programming languages

Objectives

  • Gain a historical perspective of AI and its foundations and establish the cultural background against which it has developed.
  • Know characteristics of programs that can be considered "intelligent".
  • Provide a thorough understanding of the types of problems solved using AI techniques and understand the different strategies for state space search.
  • Write prolog programs to solve AI problems.
  • Know a thorough treatment of the different types of heuristic search
  • Explore constraint satisfaction problems whose states and goal test conform to a standard, structured, and very simple representation.
  • Know classical examples of artificial intelligence such as game playing.

Course Contents:

Week / Topics / Topic Details / Reference (chapter) / Date
1 / Introduction /
  • Definition of AI, the foundation of AI, and the different application.
/ Chp.1 / 3/10
To 10/10
2,3 / Intelligent Agents /
  • define the rational agents and its environment
  • Distinguish the characteristics and structure of each intelligent agent environment.
  • Know how to describe goal-based agent
/ Chp.2 / 18/10
To
31/10
4, 5 / Problem Solving /
  • Define the main elements of that constitute a problem and its solution with different examples
  • Provide search techniques that use search tree and blind search tools
  • provide search techniques under partial information with ability to avoid repeated states
/ Chp. 3 / 1/11
To
15/11
First exam
6,7 / prolog /
  • write intelligent agent programs using prolog
/ Prolog notes / 21/11 to 4/12
8,9 / Informed search methods /
  • Provide informed search strategy that uses problem specific knowledge such as best first search, greedy best first search, A* search and others
  • Examine the nature of heuristics in 8-puzzle and explore local search algorithms
/ Chp.4 / 5/12
To
19/12
10,11 / Constraint Satisfaction Problems /
  • Know the main features of CSP and apply backtracking search for CSP
  • Apply the local search for CSP
  • Apply the constraint graph using connected components and tree decomposition
/ Chp.5 / 20/12
To
3/1
  • Second exam

12,13 / Adversial Search /
  • Explain the state of games and defining the different optimal decisions strategies such as minim ax algorithm.
  • Use pruning search strategies to reach the goal quickly such as Alpha-Beta pruning.
/ Chp.6 / 6/1
To
20/1
14,15 / Logical Agents /
  • Provide an overview of all the fundamental concepts of logical representation and reasoning
  • Provide the concepts of propositional logic PL and its semantics with depth reasoning patterns in PL.
/ Chp.7 / 21/1
To
28/1
  • Final Exam

Assessment and Grade Distribution

Assessment / Requirements / Points / Total
Attendance, Participation, / Discussions, Short Presentations / 10%
Quizzes and Home works / Unannounced Short quizzes.
Homework’s / 10%
First Exam / Multiple Choice Questions and Essay Questions. / 20%
Second Exam / Multiple Choice Questions and Essay Questions. / 20%
A Comprehensive Final examination / Multiple Choice Questions worth 50% and Essay Questions worth 50% of exam grade. / 40%
TOTAL / 100%

Teaching and Learning Methods:

  • Class lectures, lecture notes, homework assignments, and projects are designed to achieve the course objectives.
  • You should read the assigned chapters before class, complete assignments on time, participate in class among other things to understand the material. You should ask questions, whether in class or during office hours.
  • You are responsible for all material covered in class.
  • If you have any concerns, please communicate them to me in class, or by email.

Text Book and References:

Text Book
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Artificial Intelligence, A modern Approach:- Stuart Russell, Peter Norvig.Second Edition ,Prentice Hall.
[R1]
/
Lecture Notes
[R2]
/
Essentials of Artificial Intelligence, by Matt Ginsberg, MorganKaufmann,

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الرمز البريدي : 26150 هاتف : 6350522 جرش – الاردن

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