Form 4.2. Faculty member + student

Similar documents
Counseling 150. EOPS Student Readiness and Success

Laboratorio di Intelligenza Artificiale e Robotica

Agent-Based Software Engineering

Laboratorio di Intelligenza Artificiale e Robotica

MASTER OF SCIENCE (M.S.) MAJOR IN COMPUTER SCIENCE

IAT 888: Metacreation Machines endowed with creative behavior. Philippe Pasquier Office 565 (floor 14)

Axiom 2013 Team Description Paper

BA 130 Introduction to International Business

TUCSON CAMPUS SCHOOL OF BUSINESS SYLLABUS

Knowledge-Based - Systems

COSI Meet the Majors Fall 17. Prof. Mitch Cherniack Undergraduate Advising Head (UAH), COSI Fall '17: Instructor COSI 29a

SAM - Sensors, Actuators and Microcontrollers in Mobile Robots

Seminar - Organic Computing

Course Specifications

Learning Optimal Dialogue Strategies: A Case Study of a Spoken Dialogue Agent for

Lecture 1: Basic Concepts of Machine Learning

EXPERT SYSTEMS IN PRODUCTION MANAGEMENT. Daniel E. O'LEARY School of Business University of Southern California Los Angeles, California

CS 100: Principles of Computing

Module 12. Machine Learning. Version 2 CSE IIT, Kharagpur

PESIT SOUTH CAMPUS 10CS71-OBJECT-ORIENTED MODELING AND DESIGN. Faculty: Mrs.Sumana Sinha No. Of Hours: 52. Outcomes

Foreign Languages. Foreign Languages, General

Undergraduate Program Guide. Bachelor of Science. Computer Science DEPARTMENT OF COMPUTER SCIENCE and ENGINEERING

Introduction to Information System

Answer Key Applied Calculus 4

Computer Science 141: Computing Hardware Course Information Fall 2012

Courses in English. Application Development Technology. Artificial Intelligence. 2017/18 Spring Semester. Database access

Learning Methods for Fuzzy Systems

Objectives. Chapter 2: The Representation of Knowledge. Expert Systems: Principles and Programming, Fourth Edition

EECS 571 PRINCIPLES OF REAL-TIME COMPUTING Fall 10. Instructor: Kang G. Shin, 4605 CSE, ;

Action Models and their Induction

PH.D. IN COMPUTER SCIENCE PROGRAM (POST M.S.)

Radius STEM Readiness TM

Albright College Reading, PA Tentative Syllabus

Firms and Markets Saturdays Summer I 2014

Syllabus: Introduction to Philosophy

MGMT 3280: Strategic Management

Visual CP Representation of Knowledge

We are strong in research and particularly noted in software engineering, information security and privacy, and humane gaming.

UC San Diego - WASC Exhibit 7.1 Inventory of Educational Effectiveness Indicators

B.S/M.A in Mathematics

CONCEPT MAPS AS A DEVICE FOR LEARNING DATABASE CONCEPTS

BIOL 2402 Anatomy & Physiology II Course Syllabus:

MGT/MGP/MGB 261: Investment Analysis

Introduction to Psychology

ReinForest: Multi-Domain Dialogue Management Using Hierarchical Policies and Knowledge Ontology

A Reinforcement Learning Variant for Control Scheduling

Control Tutorials for MATLAB and Simulink

MBA6941, Managing Project Teams Course Syllabus. Course Description. Prerequisites. Course Textbook. Course Learning Objectives.

Pearson Grade 8 Practice And Homework

Lahore University of Management Sciences. FINN 321 Econometrics Fall Semester 2017

Class Meeting Time and Place: Section 3: MTWF10:00-10:50 TILT 221

Knowledge based expert systems D H A N A N J A Y K A L B A N D E

A simulated annealing and hill-climbing algorithm for the traveling tournament problem

STANDARDIZED COURSE SYLLABUS

ACCT 100 Introduction to Accounting Course Syllabus Course # on T Th 12:30 1:45 Spring, 2016: Debra L. Schmidt-Johnson, CPA

Maximizing Learning Through Course Alignment and Experience with Different Types of Knowledge

An Introduction to the Minimalist Program

Reinforcement Learning by Comparing Immediate Reward

Causal Link Semantics for Narrative Planning Using Numeric Fluents

Instructor: Khaled Kassem (Mr. K) Classroom: C Use the message tool within UNM LEARN, or

CRIJ 2328 Police Systems and Practices. Class Meeting Time:

Evolution of Symbolisation in Chimpanzees and Neural Nets

Some Principles of Automated Natural Language Information Extraction

An OO Framework for building Intelligence and Learning properties in Software Agents

Using dialogue context to improve parsing performance in dialogue systems

The dilemma of Saussurean communication

Class Numbers: & Personal Financial Management. Sections: RVCC & RVDC. Summer 2008 FIN Fully Online

INTRODUCTION TO CULTURAL ANTHROPOLOGY ANT 2410 FALL 2015

CS4491/CS 7265 BIG DATA ANALYTICS INTRODUCTION TO THE COURSE. Mingon Kang, PhD Computer Science, Kennesaw State University

Machine Learning from Garden Path Sentences: The Application of Computational Linguistics

Psychology 101(3cr): Introduction to Psychology (Summer 2016) Monday - Thursday 4:00-5:50pm - Gruening 413

FF+FPG: Guiding a Policy-Gradient Planner

*In Ancient Greek: *In English: micro = small macro = large economia = management of the household or family

School: Business Course Number: ACCT603 General Accounting and Business Concepts Credit Hours: 3 hours Length of Course: 8 weeks Prerequisite: None

BIOL Nutrition and Diet Therapy Blinn College-Bryan Campus Course Syllabus Spring 2011

Ph.D in Advance Machine Learning (computer science) PhD submitted, degree to be awarded on convocation, sept B.Tech in Computer science and

Penn State University - University Park MATH 140 Instructor Syllabus, Calculus with Analytic Geometry I Fall 2010

Biscayne Bay Campus, Marine Science Building (room 250 D)

Department of Computer Science GCU Prospectus

Computerized Adaptive Psychological Testing A Personalisation Perspective

CSL465/603 - Machine Learning

AQUA: An Ontology-Driven Question Answering System

TEACHING AND EXAMINATION REGULATIONS PART B: programme-specific section MASTER S PROGRAMME IN LOGIC

PBHL HEALTH ECONOMICS I COURSE SYLLABUS Winter Quarter Fridays, 11:00 am - 1:50 pm Pearlstein 308

ITSC 1301 Introduction to Computers Course Syllabus

Chapter 2 Rule Learning in a Nutshell

Linguistics. Undergraduate. Departmental Honors. Graduate. Faculty. Linguistics 1

Managing Sustainable Operations MGMT 410 Bachelor of Business Administration (Sustainable Business Practices) Business Administration Program

PELLISSIPPI STATE TECHNICAL COMMUNITY COLLEGE MASTER SYLLABUS APPLIED STATICS MET 1040

Citrine Informatics. The Latest from Citrine. Citrine Informatics. The data analytics platform for the physical world

A Neural Network GUI Tested on Text-To-Phoneme Mapping

Testing A Moving Target: How Do We Test Machine Learning Systems? Peter Varhol Technology Strategy Research, USA

WSU Five-Year Program Review Self-Study Cover Page

B.A.B.Ed (Integrated) Course

Microeconomics And Behavior

GROUP COUNSELING: THEORIES AND PROCEDURES MHS 6500 SPRING 2015 Counselor Education University of Florida Patricia Hurff, Ph.D.

MAE Flight Simulation for Aircraft Safety

San José State University Department of Psychology PSYC , Human Learning, Spring 2017

PELLISSIPPI STATE TECHNICAL COMMUNITY COLLEGE MASTER SYLLABUS APPLIED MECHANICS MET 2025

DIGITAL GAMING & INTERACTIVE MEDIA BACHELOR S DEGREE. Junior Year. Summer (Bridge Quarter) Fall Winter Spring GAME Credits.

Transcription:

Form 4.2 Faculty member + student Course syllabus for Artificial Intelligence-CS370D 1. Faculty member information: Name of faculty member responsible for the course Dr.Abeer Mahmoud Office Hours Office Number 2.501.13 Email ammahmoud@pnu.edu.sa 2. Course overview and general information: College / Department Computer Sciences and Information Sciences / Computer Sciences Course Name and code Artificial Intelligence / CS 370D Number of credit hours 3 contact hours: lecture (3)+ 1 lab 1

Program or programs that offer this course The Bachelor of Computer and Information Sciences in Computer Sciences Year/course level Level 8 / 4 th year Prerequisites for this course (if any) None Current requirements for this course (if any) None Site (to be given if not inside the main building of the institution) The Main campus 3. Objectives of the course: Understand the fundamental concepts of Artificial Intelligence Understand different methods of search and optimization in AI Able to develop small application using heuristic functions to solve any search problem in AI Understand the learning strategies Understand and implement searching techniques Understand the fundamental concept of logic in AI Understand the knowledge areas Learn PROLOG language used to implement Artificial Intelligence Systems 2

4. Course description: Week D a t e Topic Activity Intended learning outcomes methods 1 2,3 4,5,6 7,8 What is AI? History of AI. Applied Areas of AI. What s involved in Intelligence? Turing Test Intelligent Agents and environments Structure of agents Problem solving agents Solving problem by searching for solutions Uniformed search strategies (blind ) Informed search strategies (heuristic) Local search algorithm Hill- Climbing Simulated Annealing Student should read the assigned chapters before classes. Student is responsible for all material covered in the class. Instructors should teach students how to study, analyze, and think attentively and critically. Instructors should teach students to think independently and engage in group discussions. Encouragement of students to be creative in their presentation. Teaching Recognize the basics of Artificial Intelligence concepts, 1-understand meaning of intelligent agent 2-differentiate between agent types 1-Solve problems blind search algorithms 2- Solve problems heuristic search algorithms 1- Use Different AI Optimization algorithms in solving problems Class participation, Bi-weekly quizzes, POP quizzes, research paper and/or presentation given in class. Final written exam and Labs evaluation. 3

9 10,11 12,13 Local Beam Genetic Algorithms. Constraint Satisfaction Problems(CSP) Introduction to game theory First order logic Knowledge representation Forms of learning Learning from Examples Neural Network Decision Trees students to analyze data logically. Teaching students how to write programs in prolog. Use different styles of references and various scientific journals.etc. Individual counseling on research projects and scientific writing 1-Understand and differentiate between different types of logic, gaming 1- Use different knowledge representation techniques to represent a problem 1- -Solve problems learning techniques such as artificial neural network and decision trees 14 Prolog syntax and semantics Arithmetic & Boolean Expressions List Processing Robotics 1-Understand Prolog syntax 2-Write simple and advanced programs using PROLOG. 4

5. Books and references: 1. Elaine Rich and Kevin Knight: Artificial Intelligence 2 nd Ed, Tata McGraw Hill 2. Ivan Bratko :PROLOG Programming 2 nd Ed., Pearson Education 3. Stuart Russel and Peter Norvig: Artificial Intelligence A Modern Approach, 2 nd Edition Pearson 6. methods and the division of grades: method (Write an essay - test - a collective project - a final test...) 1st Med Term 2nd Med Term quiz Lab Week 7th week 12th week 9 th week exam Grade 10 20 Percentage from overall grade % % 10% 20% Comments Final exam (Theory) Two academic hours. Total After 40 100 40 100 7. Instructions (if any): 5