* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Download CS 231 - Introduction to Artificial Intelligence
Survey
Document related concepts
Embodied cognitive science wikipedia , lookup
Artificial intelligence in video games wikipedia , lookup
Technological singularity wikipedia , lookup
Collaborative information seeking wikipedia , lookup
Expert system wikipedia , lookup
Philosophy of artificial intelligence wikipedia , lookup
Ethics of artificial intelligence wikipedia , lookup
Intelligence explosion wikipedia , lookup
Existential risk from artificial general intelligence wikipedia , lookup
Transcript
CS 231/CMPE 231 : Introduction to Artificial Intelligence Instructor’s Name: Office No. & Email: M. M. Awais 224, [email protected] Office Hours: TBA TA for the Course: TBA Year: 2003-2004 Quarter: Winter Category: Junior Course Code (Units) CS 231/CMPE 231 : Introduction to Artificial Intelligence (4 Units) Course Description This course will introduce the basics of artificial intelligence (AI), its scope and application domain. The course will cover topics such as knowledge representation, propositional logic, predicate calculus, search methods, learning, languages for AI programming, natural language representation, automated reasoning, knowledge based systems and project implementation and knowledge application. Core/Elective Elective Pre-requisites CS courses that include topics of general computing, data structures and algorithms. Familiarity with at least one programming language and environment. Goals 1. To introduce the principles of AI methods. 2. To equip students with the developments, justifications, implementation, and use of representational, formalism and search methods. 3. To provide an opportunity to students to learn methods most useful under complex computational uncertain, and vague situations. TextBooks, Programming Environment, etc. A. Artificial Intelligence: Structures and Strategies for Complex Problem Solving. (George F. Luger, and William A. Stubblefield). B. Mathematical Methods in Artificial Intelligence. (Edward A. Bender). C. Principals of Artificial Intelligence and Expert Systems Development. (David W. Rolston) D. Introduction to AI and Robotics (Robin R. Murphy) Lectures Two Sessions of 100 Minutes each Grading Assignments/Projects Quizzes/Mini-Tests Mid-Term Exam/Term Test Final Exam 15% 20% 30% 35% CS 231/CMPE 231: Introduction to Artificial Intelligence Year: Quarter: Module 1 2 Topics Introduction History Applications Future Knowledge Representation with AI Sessions 1 2, 3 2003-2004 Winter Readings A) Chapter 1 A) Chapter 2 applications Propositional Logic Predicate Calculus 3 Search Methods 4 A) Chapter 3, 4, 5 8, 9, 10 A) Chapter 6, 7 Introductions State Space Search Depth First Search Breath first search Heuristic search Hill climbing Best first search A* method Adversary search Alpha Beta Pruning Min Max Approach Control and implementation of search AI Languages 4, 5, 6, 7 Standard vs AI languages Prolog/LISP (Visual or otherwise) Mid - Term Exam 11 CS 231CMPE 231: Introduction to Artificial Intelligence Year: Quarter: Module 5 Topics Knowledge Database representation Introduction Expert System Design Architecture Case Study (MYCIN) Parallel Knowledge Data Discovery 6 Natural Language Processing Introduction Syntax Semantics and Pragmatics 7 AI and Robotics Learning Paradigms (Some Sessions 2003-2004 Winter Readings 12, 13 A) Chapter 8 14 A) Chapter 10 15 Handouts(D) 16, 17 A) Chapter 12 18 B) Chapter 14 (p 605-607) 19, 20 Handouts (D) examples) Computer Vision Agents (definition, design and working) Final Exam