UNIVERSITY OF DAYTON

CPS 480/580:  Introduction to Artificial Intelligence

Spring Semester 2011      3 credits  T Th     1:30-2:45pm

207 Miriam Hall

Professor:  Dr. Jennifer Seitzer Office: 144 Anderson Hall Email:  seitzer@udayton.edu Course Web Page:            http://homepages.udayton.edu/~jseitzer1/cps480 Phone: (937) 229-2197 *Office Hours: Wed:   11-2pm Thur: 3-4pm By appointment

Mailing Address: Dr. Jennifer Seitzer, Associate Professor Computer Science Department University of Dayton 300 College Park Dayton, OH 45469-2160

---

Syllabus

Description and Motivation

Intelligence is an elusive concept. Artificial intelligence is more elusive because, here, we attempt to simulate this unquantifiable and uncodifiable dictating force of humans. We use many techniques to do this, none of which is all-inclusive, but all together, continue to give us more effective and smarter systems.

We will study these techniques. Primarily, in this semester, we will focus on traditional “good old-fashioned AI” (GOFAI) which concentrates on search and knowledge representation. We will also introduce the concept of an agent: any entity that perceives its environment through sensors and acts upon or changes its environment through actuators or effectors. In this class, we will consider many manifestations of agents. We will approach the fundamental techniques of classical artificial intelligence, knowledge representation and heuristic search strategies, using agents to implement, understand, and elucidate. We will learn the basics of the programming languages LISP, PROLOG, and SPARQL and examine how knowledge representation on the Semantic Web is represented. We will finalize our study by considering embodied intelligent agents in the form of robots.

Required Text:

Required Text: Artificial Intelligence A Modern Approach 3^rd Edition

By, Stuart Russell and Peter Norvig

ISBN # 0-13-103805-2

Course Objectives

• To be able to define Artificial Intelligence. This includes:

o describing typical AI tasks

o stating techniques required to solve AI problems

o knowing its successes and prospects

• To learn basic heuristic search strategies and algorithms
• To understand the techniques underlying game programs such as chess and bridge
• To learn knowledge representation techniques including logic, fuzzy logic, nonmonotonic reasoning, frames
• To understand strategies of reasoning: forward chaining, backward chaining.
• To be exposed to intelligent agents, both software and physical robots
• To program the techniques and algorithms studied in class into working systems

Helpful Materials

Extra Credit Form

Program and Lab Cover Sheet

PROLOG Interpreter

PROLOG Interpreter WINZIP format-- Please Download and Unzip

Graduate Student Term Project