Artificial Intelligence M.C. Juan Carlos Olivares Rojas Course Syllabus January, 2009.

Slides:



Advertisements
Similar presentations
Operating Systems M.C. Juan Carlos Olivares Rojas Course Syllabus January, 2009.
Advertisements

Of 17 course outline. of 17 marek reformat ecerf building, w ece 627, winter'13.
CSCE 210 Data Structures and Algorithms
CS 331 / CMPE 334 – Intro to AI CS 531 / CMPE AI Course Outline.
© 2002 Franz J. Kurfess Introduction 1 CPE/CSC 481: Knowledge-Based Systems Dr. Franz J. Kurfess Computer Science Department Cal Poly.
CS : Artificial Intelligence: Representation and Problem Solving Fall 2002 Prof. Tuomas Sandholm Computer Science Department Carnegie Mellon University.
© 2001 Franz J. Kurfess Introduction 1 CPE/CSC 580: Knowledge Management Dr. Franz J. Kurfess Computer Science Department Cal Poly.
1 SWE Introduction to Software Engineering Fall Semester (081) King Fahd University of Petroleum & Minerals Information & Computer Science.
CS5201 Intelligent Systems (2 unit) Semester II Lecturer: Adrian O’Riordan Contact: is office is 312, Kane
METU Computer Engineering Department
CSE (c) S. Tanimoto, 2008 Introduction 1 CSE 415 Introduction to Artificial Intelligence Winter 2008 Instructor: Steve Tanimoto
Network Management M. Sc. Juan Carlos Olivares Rojas
COMP 151: Computer Programming II Spring Course Topics Review of Java and basics of software engineering (3 classes. Chapters 1 and 2) Recursion.
Teaching Teaching Discrete Mathematics and Algorithms & Data Structures Online G.MirkowskaPJIIT.
CSCI 347 – Data Mining Lecture 01 – Course Overview.
Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall 1 Introduction to CPSC Introduction to CPSC Information Technology.
Introduction to Network Security J. H. Wang Feb. 24, 2011.
Calculus I – Course Syllabus Class Periods: 10:00am-10:50am MTWF Classroom: Thompson Hall 303 Instructor: Mei Q. Chen, Thompson Hall 328
Introduction to Discrete Mathematics J. H. Wang Sep. 14, 2010.
CS 390 Introduction to Theoretical Computer Science.
Syllabus Faculty of Applied Engineering and Urban Planning Civil Engineering Department Lecture - Week 1 2 nd Semester 2008/2009 UP Copyrights 2008 Introduction.
Course ‘Data structures and algorithms – using Java’ Teaching materials and presentation experience Anastas Misev Institute of Informatics Faculty of Natural.
Informatic Aduting K1 Classroom, Monday to Friday at 10:00 Instructor: M.C. Juan Carlos Olivares Rojas
Network Security I M.C. Juan Carlos Olivares Rojas Course Syllabus January, 2009.
Assoc. Prof. Abdulwahab AlSammak. Course Information Course Title: Artificial Intelligence Instructor : Assoc. Prof. Abdulwahab AlSammak
CS-2851 Dr. Mark L. Hornick 1 CS-2852 Data Structures Dr. Mark L. Hornick Office: L341 Phone: web: people.msoe.edu/hornick/
CS 179.4/215 3D Modeling & Animation DISCS. Course Description This course will focus on the theories of geometry, algorithms in computer graphics and.
Introduction to ECE 2401 Data Structure Fall 2005 Chapter 0 Chen, Chang-Sheng
COMP 304: Artificial Intelligence. General Lecturer: Nelishia Pillay Office: Room F3 Telephone:
© 2002 Franz J. Kurfess Introduction 1 CPE/CSC 481: Knowledge-Based Systems Dr. Franz J. Kurfess Computer Science Department Cal Poly.
KNOWLEDGE BASED SYSTEMS
ITIS 4510/5510 Web Mining Spring Overview Class hour 5:00 – 6:15pm, Tuesday & Thursday, Woodward Hall 135 Office hour 3:00 – 5:00pm, Tuesday, Woodward.
Structured Design of Algoritms M.C. Juan Carlos Olivares Rojas Course Syllabus January, 2009.
Notes for Week 11 Term project evaluation and tips 3 lectures before Final exam Discussion questions for this week.
Introduction to Artificial Intelligence CS 438 Spring 2008.
Network Management M. Sc. Juan Carlos Olivares Rojas
General Information Course Id: COSC6368 Artificial Intelligence Professor: Ricardo Vilalta Classroom:AH 110 Telephone: (713)
Introduction: What is AI? CMSC Introduction to Artificial Intelligence January 3, 2002.
Workshop of Administrative Informatic I LABA Classroom, Tuesday and Thrusday at 18:00-20:00, Wednesday at 18:00-19:00 Instructor: M.C. Juan Carlos Olivares.
Introduction: What is AI? CMSC Introduction to Artificial Intelligence January 7, 2003.
Mathematical Logics Course introduction. Forehead  Lecturers: Fausto Giunchiglia, Vincenzo Maltese  Scheduling: Tuesday 8:30-10:30, room A107 Thursday.
Computing & Information Sciences Kansas State University Wednesday, 04 Oct 2006CIS 490 / 730: Artificial Intelligence Lecture 17 of 42 Wednesday, 04 October.
1.  This course covers the mathematical foundations of computer science and engineering. It provides an introduction to elementary concepts in mathematics.
Definition and Technologies Knowledge Representation.
Computing & Information Sciences Kansas State University Friday, 13 Oct 2006CIS 490 / 730: Artificial Intelligence Lecture 21 of 42 Friday, 13 October.
Introductory Lecture. What is Discrete Mathematics? Discrete mathematics is the part of mathematics devoted to the study of discrete (as opposed to continuous)
CMPT 463 Artificial Intelligence Instructor: Tina Tian.
BMTS Computer Programming Pre-requisites :BMTS 242 –Computer and Systems Nature Of the Course: Programming course, contain such as C, C++, Database.
Chapter 13 Artificial Intelligence. Artificial Intelligence – Figure 13.1 The Turing Test.
Introduction to Artificial Intelligence Heshaam Faili University of Tehran.
CS140 – Computer Programming 1 Course Overview First Semester – Fall /1438 – 2016/2017 CS140 - Computer Programming 11.
CSCE 210 Data Structures and Algorithms
CENG 707 Data Structures and Algorithms
Computer Engineering Department Islamic University of Gaza
Artificial Intelligence
Syllabus Introduction to Computer Science
General Information Course Id: COSC4368 Artificial Intelligence Programming Time: Mondays and Wednesdays 1:00 PM – 2:30 PM Professor: Ricardo Vilalta.
ece 720 intelligent web: ontology and beyond
Principles of Computing – UFCFA Lecture-1
CSC 361 Artificial Intelligence
Artificial Intelligence (CS 461D)
Artificial Intelligence (CS 370D)
First work in AI 1943 The name “Artificial Intelligence” coined 1956
Lecture 1: Introduction
CSE 415 Introduction to Artificial Intelligence Winter 2004
Workshop of Administrative Informatic II
CSE 415 Introduction to Artificial Intelligence Winter 2003
Principles of Computing – UFCFA Week 1
CSE 415 Introduction to Artificial Intelligence Winter 2007
CMPT 420 / CMPG 720 Artificial Intelligence
Presentation transcript:

Artificial Intelligence M.C. Juan Carlos Olivares Rojas Course Syllabus January, 2009

Outline Introduction Topics Grading Recommendations References

Introduction The students will know in detailed form the construction and working of intelligent systems The students will programming and knows diferent kind of languages and applications for artificial intelligence

Basic Concepts 1.1 Basic Concepts 1.2 Applications 1.3 The Intelligent Systems and Learning 1.4 Semantic Networks 1.5 Match and Description Method 1.6 Analogy Problem 1.7 Abstraction Recognition 1.8 Knowledge Interpretation

Networks and Basic Search 2.1 Blind Methods 2.2 Heuristic Method 2.3 The Best Path 2.4 Redundant Paths 2.5 Trees and Search with Adversary Algorithmic Methods 2.6 Trees and Search with Adversay Heuristic Methods

Logic 3.1 Knowledge Representation 3.2 Preposition Logic 3.3 Predicate Logic 3.4 Automatic Deduction

Rules and Chained Rules 4.1 Deduction Systems 4.2 Reaction Systems 4.3 Progressive and Regressive Chained 4.4 Cognitive Modeling 4.5 Problem Solving Models

Lisp Programming 5.1 Introduction 5.2 Structures 5.3 Basic Operations 5.4 Control Structure 5.5 Mathematic Operations 5.6 Predicate Function 5.7 Relations and Sets 5.8 Input and Outputs 5.9 Implementation 5.10 Backup and Recovery

Grading Only two partial and one Final Exams (only the last partial). 70% Partial Exam 30% Homeworks and Practices 10% Quizzes

Recommendations The classes begin at 19 to 21 hours at 6C Classroom on Tuesday and at Electronic Lab on Thursday The advisory should be by , Instant Messenger or by another electronics media MSN: Skype: juancarlosolivares Web:

Recommendations The homework must be delivery in Classroom or before class throught moodle or by CD. The rubric of work contains: –Cover –Abstract –Introducction –Development* –Conclusions –References**

References Nilsson, N. (2001). Artificial Intelligence. A New Synthesis. McGraw-Hill. Russel, S. and Norving, P. (2004). Artificial Intelligece. A New Approach. Pearson Prentice Hall. Winston, P. (1998). Artificial Intelligence. 3rd. Ed., Adisson-Wesley.

References Knight, R. (1997). Artificial Intelligence. 2nd Ed. McGraw-Hill. Tanimoto, S. (1998). The Elements of Artifical Intelligence using Common LISP. W. H. Freeman Company.

Questions?