Terry L Zimmerman
Examines current topics and issues associated with computing and software systems. Offered: AWSpS.
Artificial intelligence has a unique place in science, sharing borders with mathematics, computer science, philosophy, psychology, biology, cognitive science and others. This course will introduce the basic principles in A.I. research. We will cover simple knowledge representation schemes, problem solving paradigms, constraint propagation, search strategies, logic and graphical models. You will learn the foundational principles that drive A.I. applications such as intelligent agents for decision-making, automated reasoning, game playing, automated planning and scheduling, basic robotics, and as time permits, machine learning. Basic programming exercises will give you practice in implementing some of these systems.
Student learning goals
Students will have an understanding of the basic issues and forms of knowledge representation.
An understanding of blind and heuristic search strategies and be able to construct programs that execute them.
An understanding of topics such as minimax, resolution, etc. that play an important role in AI programs.
An understanding of automated planning, planning problem representation and solution methods.
General method of instruction
Instruction methodology will combine lectures, text assignments, in-class exercises, and programming projects.
CSS 342 / 343 Data Structures, Algorithms, and Discrete Mathematics
Class assignments and grading