[Jared Russell]

Thank you for posting this!

This is definitely a novel way of looking at things in FRC. I work in the artificial intelligence field, and one constant source of frustration is when people want to fit the square peg of automation into the round hole of problems that are currently better solved by human reasoning. Yes, without at least trying we won't advance the state of the art in AI, but at the same time people seem to be keen on taking humans out of the loop for no convincing technical reason. Case in point: much current research seeks to make currently teleoperated UAVs fully autonomous. But each UAV needs a ground crew of probably 50 people to stay operational; is eliminating the one pilot really the lowest hanging fruit? Play to the strengths of each part of the team! But I digress...

Back to your paper, I think that some of your points could stand to be fleshed out just a bit more - I'm not sure that you've identified the best possible "square peg" and "round hole" in this case. You claim that pattern recognition tasks are better solved by humans than by computers, but I don't believe this to be true for a large class of problems. For example, in Aim High in 2006 I would argue that auto-targeting bots could outshoot even the best driver's aim. Tracking a known, invariant object has been done effectively using a variety of techniques in computer vision. Now, when you are talking about avoiding other teams' robots that vary widely in form and function, then I would agree with you that humans (currently) do it better.

You also talk about how computers can do a better job of decision making at a tactical level because they are undeterred by things like distractions, emotion, etc. This is a very interesting question that has significant repercussions in the defense community (as soldiers/pilots are exposed to the elements, at what point does their cognitive ability become inferior to a machine's?).

However, I think that there are some issues that will prevent your robot from ever being a more effective strategist than a person. In order to come up with an effective strategy, you need to know the full state of the field at a moment in time. Knowing the locations of goals and robots is NOT the exhaustive list of the elements of this state. You also need to know something about intent - yours, your teammates', and your opponents'. Even if you acknowledge that humans can estimate intent better than a machine, how are they going to convey their estimations to the robot in a reasonable amount of time? And how is the decided-upon strategy going to make it back to your teammates?

My comments here aren't meant to attack your paper; rather, I hope that you can use them to improve it! This is a really radical way of thinking about human-computer interactions in FRC that I don't think is far off from being quite useful in the right situations.