An overview of the field of artificial intelligence, including intelligent agents, knowledge-based systems, neural networks, genetic algorithms, natural language processing, robotics, computer vision, virtual and augmented reality, philosophy and ethics of artificial intelligence, and AI Programming. (Offered fall semester, even years.)

CIS 385 Data Structures and Algorithms

P. Norvig and S. J. Russell, Artifical Intelligence: A Modern Approach, 3^rd edition, Upper Saddle River, N.J: Prentice Hall, 2010

Eugene G.Rohrbaugh, Professor of Computer Science

Optional 400 level course for Information Science majors.

To successfully complete this course, students will:

1. explain basic concepts and techniques of AI through definitions and examples.
2. summarize the history and current status of AI.
3. use objective facts about current AI technologies to project plausible future trends.
4. analyze problems and recommend AI-based solutions when appropriate.
5. develop documented and working code exhibiting AI methods.
6. summarize the philosophical, moral, and ethical issues confronting people doing AI work.

1. Philosophical foundations
2. Intelligent agents
3. Search
4. Knowledge representation and reasoning
5. Inference
6. Probabilistic/stochastic techniques
7. Near-future trends in AI