Update June 1, 2019: the class number has changed to CS 287H.
In addition to taking STAT 210A this semester, I took CS 294-115, Algorithmic Human-Robot Interaction, taught by Professor Anca Dragan. I will first provide a summary of what we did in class, roughly in chronological order. Then I would like to discuss what could be improved for future iterations.
The first day presented, as usual, the enrollment surge, which is either a good thing or a bad thing. But for being able to find a chair in the classroom, it’s a bad thing. I arrived a few minutes before class started (which is actually late for the first day) and found a packed room, but fortunately my two sign language interpreters had booked a seat for me.
I felt bad for that. If I’m the last to arrive and all the chairs are taken, I have no problem sitting on the floor or standing up. It’s OK. Fortunately, the number of students eventually dropped to 34 by the end of the course, but for the first few weeks, we had a lot of students sitting on the floor or standing by the door. The two sign language interpreters took up two seats, so I worried that I was inconveniencing the other students. Fortunately, no one seemed to be angry, and Professor Dragan seemed to be OK with it. In fact, at the start of the semester, she sent me an email asking how the course was going, if she was talking too fast, etc. I remember two other professors contacting me that way: Sarah Jacobson for Microeconomics and Wendy Wang for Bayesian Statistics, and I like it when professors do that. I responded saying that she was doing just fine and that any limitation in my ability to understand material was mostly out of her control.
In CS 294-115, much of the first half of the semester consisted of lectures on standard robotics topics, particularly motion planning and trajectory optimization. This is also an HCI course, and we had lectures on experimental design and learning from demonstrations (which are often human-led). The most concise way to describe this class is probably a cross between CS 287, Advanced Robotics, and CS 260, the Human-Computer Interaction course at Berkeley. I think a lot of computer science PhD students took CS 294-115 to satisfy their PhD breadth requirements. I would, of course, take it even if it didn’t satisfy my requirements.
As I quickly learned, one of the most controversial aspects of CS 294-115 are the quizzes. Every few classes, Professor Dragan would set the first 5-10 minutes aside for a quiz, which typically asked basic questions about topics covered in the previous lectures. Each quiz was graded on a three-point scale: minus, check, and plus. I earned one plus and three checks on the four “normal” quizzes we had.
For one of the quizzes, the class as a whole did poorly (a third minus, a third check, and a third plus). Probably the reason for this is that the question was about the reading for the class, specifically, the Maximum-Entropy Inverse Reinforcement Learning paper. Before the quiz, Professor Dragan smiled and said something similar to: “if you didn’t do the reading, try to say anything relevant.” Gee, it looks like the do-your-readings rule doesn’t even apply to Berkeley graduate courses!
We had a make-up quiz, but I still only earned a check. Ugh.
Regardless of whether this class turns into a seminar or a lecture (which I’ll discuss later in this article) I personally think the quizzes should be abolished. Professor Dragan also commented in class that some students thought quizzes did not belong in a class like this. We’re “not in high school,” as some succinctly put it.
As one can tell from reading the syllabus online, aside from the lectures, we also had a lot of classes devoted to student presentations about research papers. For each paper, we had a PRO and a CON presenter. Their names are self-explanatory: the PRO presenter talks about the paper as if he/she had written it, while the CON presenter provides constructive criticism. I liked this part of the class, though there are some inherent weaknesses, such as scalability.
I had to wait a while; it wasn’t until November 15 that I got to present. I was assigned to be the CON presenter for a very interesting (and award-winning!) paper Asking for Help Using Inverse Semantics.
In every talk, I always need to think of several jokes to say. The logic is as follows: I am at the bottom of the social hierarchy when it comes to anything related to popularity. Thus, when I’m giving a talk to a class or some audience, this is one of the few times where people are actually going to bother to listen to what I have to say. In other words, I really can’t afford to waste my chance to give a positive impression. One way to make a good impression is to give a talk about something really positive, such as if I came up with a really new algorithm that people will love. Unfortunately, aside from the really top-tier stuff, I think it’s hard to distinguish oneself with the content of the talk (especially if it’s not about work I did!) so the next best thing that really helps is being reasonably funny.
Thus, I came up with the following tentative plan: since it’s election season, let’s have “Anca for President”! I would include an image of a bunch of faces going left to right, in order of how much respect I have for the person. Clearly, Professor Dragan would be at the rightmost spot (most respect), and someone like Putin would be at the leftmost spot. I think if I showed something like that in class, it would elicit considerable laughter and raise talks of “Anca for President!” even though she’s not Constitutionally eligible. Unfortunately, the paper I presented didn’t really make this joke fit in the talk well. Combined with the fact that the candidate who everyone opposed won the election … never mind.
Instead, I made a joke about how humans differ in their “level of altruism.” In CS 294-129, for which I was the GSI, a student asked a question on Piazza about how to use Jupyter Notebook. It was a really stupid and shallow question, but I couldn’t resist answering it to the best of my ability. But then Professor Canny responded with a far stricter (but also far more helpful!) answer, along the lines of “no one can help you with that much information […] saying this is a waste of time […]”. It was pretty clear that Professor Canny and I have drastically different styles, and I tried to put that in a humorous perspective. I think it worked well, but the text was admittedly too small to see well, and Professor Dragan docked me for it during her email to me immediately after the talk.
Unfortunately I was scheduled as the fourth presenter that day, which is easily the worst slot to be in for this class. As luck would have it, the other three presenters went over their time (I sarcastically thought: “big surprise”), meaning that I got to be the first presenter during the following class.
The class after my actual presentation was the one before Thanksgiving, and it was a special one where Professor Dragan ran an experiment. Rather than have the usual PRO/CON presenters, we would instead split into small groups for discussion. You can imagine how much I “liked” that. To the surprise of no one, my sign language interpreters could not understand or follow the discussion well, and neither could I. But maybe I’m just a lonely Luddite. It seemed like the other students enjoyed that class.
After the Thanksgiving “break”, we had class presentations during the final week. I’m not sure if there’s something about the aura in our class, but there’s so much more humor compared to the Deep Neural Networks presentations from CS 294-129. Seemingly everyone had a joke or did something that caused laughter. Here are a few that I remember:
- Explicitly saying a joke. These are the best kind and the ones I try to do every time, for reasons described earlier.
- Showing a funny video.
- Performing a funny gesture.
- Complaining about the 4-minute time limit and watching as Professor Dragan sneaked closer and closer to the presenter to cut off the talk.
- Having multiple phones time the talks (Professor Dragan’s and the presenter’s) and having them both ring after 4 minutes.
- Grabbing Professor Dragan’s laptop after the talk was over, thinking it was theirs.
The laughter was contagious and this is definitely something positive about the class. My project presentation, incidentally, was about human gameplay to boost Atari game play agents. I have some code that I’ll hopefully release soon.
After the project presentations, we had to work on our final reports (5 page maximum). Here’s a tip for those who need more space, which should be everybody: use IEEE Conference-Style papers. The font size is small, and when you expand the LaTeX coding to reach the maximum margins, you get a lot of information packed into five pages.
All right, that was the class, but now what about some feedback? Professor Dragan said she plans to teach this class again under the new “CS 287H” label. What could be better for future semesters? In my opinion, the most important question to ask is whether the class should be structured as a seminar or a lecture. Doing it half-seminar, half-lecture as we had is really awkward.
I am inclined towards turning CS 294-115 into a standard lecture course, given my problematic history with seminars. Yes, I know I’ve complained a lot about not being able to follow technical lectures, but seminars are still, on average, worse.
The decision is obviously up to Professor Dragan. If she wants to keep it as a seminar, I would highly encourage:
- establishing a strict enrollment limit with no more than 30 students and requiring prospective students to fill out a detailed form describing how they can contribute to the class. There are several classes which do this already so it’s not unusual. The enrollment limit is necessary because far more students will sign up next year. Why? It’s simple: robotics is very popular and Professor Dragan is very popular.
- enforcing time limits better. There were many times when students, for both PRO/CON presentations and final project presentations, exceeded their allotted time.
If CS 294-115 turns into a normal lecture, then:
- introduce problem sets and a midterm to test knowledge instead of relying on shallow quizzes. This will require GSIs, but by now there are plenty of students who can do that job. This will mean more work for the students, but CS 294-115 probably needs more work anyway. It’s listed as 3 credits, but I think it’s more accurate to call it a 2.5-credit class.
Regardless of the class style, I have an idea if quizzes have to remain in CS 294-115. To fix the problem of students not reading papers beforehand, let’s have quizzes for all the paper readings. In fact, the student presenters can create them! They can do the grading and then forward the results to Professor Dragan to minimize her workload.
Don’t misunderstand what I’m saying. Throughout the class, I looked at all the papers, but I mostly read only the abstract plus the first few introductory sections. I wanted to read these papers in detail, but there’s a tradeoff. If I can spend four hours the night before class working towards important research, I’m going to prefer doing that over reading a paper without hesitation.
My final suggestion for the class is about the project presentation sign-up process. We had a class spreadsheet and had to sign up for one of the two days. Instead, let’s randomly assign students to presentation times and make slides due on the same night for everyone.
Well, that’s all I want to say about CS 294-115 now. This is just one person’s opinion and others will no doubt have their own thoughts about the class. I’ll check the future course websites now and then to see if there are any interesting changes from the version I just took.
Professor Dragan, thanks for a fun class!