CSCI 2951X: Reintegrating AI
The goal of AI has been to build complete intelligent agents, yet the field has been fragmented into a collection of problem-specific areas of study. We will first spend a few weeks in lecture covering a new approach to integrating existing AI subfields into a single agent architecture, and remainder of the semester on self-directed, semester-long research projects.
Grading will be based on a mid-semester project proposal, and a substantial open-ended final project. The projects will be multi-disciplinary in nature but students will have the opportunity to work in small groups, so they need not necessarily have expertise in the relevant areas. All students need special permission to enroll; advanced undergraduate students welcome.
The 2018 incarnation of this course was a reading seminar; the old website and reading lists are here.
The first class is on Thursday January 21st, and the class is on a Tuesday-Thursday schedule, from 1:00pm to 2:20pm. The class is asynchronous: lectures will be delivered via Zoom (at this link) at the scheduled date and time, and you are welcome to attend live, but recordings will be posted. After the first few lectures, you will break into project groups, and we will arrange asynchronous check-ins.
Your project will be a substantial creative and original piece of work. I expect you to design and implement theory and experiments studying some algorithm or model that is aligned with the course content - i.e., a model that integrates at least two aspects of AI research in an interesting way.
I expect it to have approximately the length, form, and content of a conference paper at a good AI conference (though it need not be publishable). That means careful, clear, and precise writing, a well-formalized and thoughtfully evaluated point, and thorough referencing throughout. It does not necessarily have to be an original contribution, although that would be nice. If it is not, then I expect at least an original evaluation that is relevant to our topic (e.g., an existing algorithm is tried in a new domain or addresses a setting that speaks to what we have discussed).
The study will be graded on insight, completeness, and clarity. These studies can be completed in groups of between 1 and 4 people. Undergraduates taking the course should work in groups of at least 3.
The project accounts for 100% of your grade and is due at the end of the reading period (April 19th).
There is an intermediate deadline: a 2-page project proposal due by approximately mid-February, which identifies the topic, names the group, and sketches out what you hope to accomplish in the study. I will use these to discuss the project with each group to make sure they're on an appropriate path.
General background for embodiment and general AI (all quite dated):
MDPs and RL:
Abstraction in RL:
Natural Language for MDPs:
Readings from the following books are recommended for more in-depth engagement with the topic, though note that all of these are now dated:
These books and readings will be of interest to students who want to understand the probabilistic foundation of AI more deeply: