| Prof. Luke Hunsberger | My Web Page |
| Artificial Intelligence (AI) has a history of algorithmic innovations stretching back to the mid-1950s. Over the ensuing decades, techniques in AI have enabled advances in a wide variety of areas, including voice recognition, automated reasoning, vision processing, planning and scheduling, game-playing programs, and many more. This intensive focuses on using Temporal Networks to reason about time. Students will work in small collaborative groups on programming projects throughout the semester aimed at empirically evaluating existing algorithms for different kinds of temporal networks. Particular attention will be paid to ensuring that all empirical evaluations are reproducible. The projects completed during the semester will be used to populate a new (virtual) Temporal Reasoning Laboratory (TRL) . |
| There are no textbooks for this course. Any readings/handouts/supplementary materials needed will be provided on the course Moodle page. |
| Although the focus of this intensive is not on exams, there will be a midterm exam that will cover the basics of Simple Temporal Networks and algorithms for processing them. The exam will count for 20% of the grade. The remaining 80% will be based on contributions to programming projects during the course as well as presentations toward the end of the course. |
| The calendar section below will grow incrementally as we progress through the semester. |
Wednesdays
| Sept. 1 | Introduction to Temporal Networks |