Swarm Control at AAAI Fall Symposia

Later this week, I'll be giving a talk at a symposium on Human Control of Bio-Inspired Robot Swarms (part of this year's AAAI Fall Symposium Series).  I like the AAAI symposia, because they're a really good place for position papers and preliminary work: you can put your ideas out there, get some good feedback, and at the same time put it in an archival place where people can cite it if they find it useful and inspiring.  I think it's also one of the things that keeps the AI community from being scoop-fearful like many other communities.

Anyway, my talk is about an application of my continuous space abstractions and Proto that should be pretty obvious: controlling large swarms of robots.  We published a journal paper aiming in this direction a couple of years ago, talking about how viewing a swarm as a "material" flowing through space makes it very simple to create complex swarm behaviors.  Rather than worry about all the individual robots and how they should interact, you specify how regions should stretch and squish and flow.

This isn't entirely new---other people have used continuous space models as well, though in a much more control theory or partial differential equations way.  The nice thing about Proto is that once you've got a behavior specified, you can build on it, modulate it by choosing which robots are participating, compose it with others, etc., and it's all very simple and easy to predict what's going to happen.  That's how you can build up such complex behaviors so quickly and easily---once you've got a few building blocks, you can go wild putting them together.

Well, this week's paper is pushing that work forward, asking the question: What's a good interface for letting ordinary people talk about what they want their swarm to do?  I'm proposing that a good starting point is a sort of "command and control" model where you break your swarm into units, and then talk about who's supposed to stick together, where they're supposed to move, and how much they should be long & thin vs. thick and fat.  Or to be more precise: specifying the first three moments of the swarm distribution for each unit.  That makes it easy to make formations like these:

Swarm moving in a dumbbell formation, and another in a chevron formation.

There's a bunch of other thoughts in there, and proposals for how we can turn this idea from early work into something practical for people to use with swarms.  Not that there is much in the way of actual swarms out their yet either (with some elegant notable exceptions), but that's only a matter of time and cheapening hardware, and there's a lot of folks working on that...

I'll post the paper after the talk is given.

Congratulations to Noah Davidsohn!

Following up on last week's post about characterization, let us celebrate Noah Davidsohn's successful Ph.D. defense.  Ron Weiss and I have been co-advising Noah's work on the characterization project, where he has done all of the wet-lab work and contributed that perspective into the experimental planning and analysis.  Noah presented a quite clear and coherent discussion of the scientific journey of the project, all the way up to the ultimate results that I previewed here last week.  The dark cloaked forms of the Thesis Committee now draw aside, and all that remains to the acolyte is to finish the Document itself...

Congratulations, Noah!

Progress in Characterization...

Normally I wouldn't share a significant unpublished result on this blog, but last week we showed this off at a program meeting, so the cat is already mostly out of the bag.  To make a long story short, all of the hard work we've been doing on characterization of devices in synthetic biology is beginning to pay off.  I've talked about this a couple of times before, on the struggle to make good models of biological devices and on the new characterization protocols we developed so that we could study devices quickly and precisely.

Now, it seems to all be coming together nicely, and we've gotten a few beautiful results like this:

I'm not going to try to explain it all here (well, unless somebody actually asks for details in the comments), but the important things to understand are this:

1. The circles are our predictions, and the crosses are the experimental data
2. The colored areas we have confidence to predict in, the grey areas we don't
3. Our predictions are really, really close to the actual behavior.

That's all I'll say for the moment, but look for a publication will full details appearing Real Soon Now... and I'm damned excited, because if the future work keeps going in the direction these results indicate, it opens the door for massively more complex biological systems and justifies the whole design tools thrust that we've been making at BBN...

That new proposal smell...

Last week, my collaborators and I sent off a full proposal and a pre-proposal.  I'm quite proud of both of them: they both build logically on what we have done before, have clear and achievable research programs, and aim towards applications that people care about.  Maybe you'll hear about them again, and maybe you won't, depending on whether the folks on the receiving end agree with us...

What I want to talk about here, though, is that wonderful new proposal smell.  When I'm writing a proposal that I'll be a PI for, I really have to fall in love with the ideas.  I just can't see sending in a second-rate proposal, to do something that you aren't all that enthusiastic about, and I have to think that the reviewers would be able to smell that on one's proposal as well.  Oh, I've been an nth writer on proposals I wasn't enthusiastic about before, but that's different than being a PI, the Primary Investigator, the one leading the charge and holding the bag if things go wrong.

So when you start working on a proposal, there's the foundation you've got and the target you're writing to, and this dance where you try to bring the two together, and figure out how to sell your ideas to the folks on the other end, whose purposes are not your own.  It would be easy to be cynical about it, I think, and to view the process as some sort of money/power game.  And I suspect that it actually is in some of the really giant-money high-stakes stuff, like where Congress gets directly involved.  But in the world that I play in, I don't think that's the case.  And it's not just about marketing, either.

Rather, I look at proposal-writing as a distinct part of the scientific process.  When you're doing science, you need to understand not just "What is my idea?" but more importantly, "How does my idea relate to what else is out there?" and "What difference does it make if my idea is true?" Sometimes this can be related directly to some sort of real-world application (as is the case with my work on energy management).  Sometimes it's indirect, where you might end up affecting the world someday, but someday is likely rather far away.  Sometimes this just relates to how we understand the world we live in, where we come from, and where we're going (whenever I start to fret too much about real-world applications, I remember that General Relativity, one of the most significant intellectual developments of the 20th Century, has only recently reached into the practical world of our daily lives via the GPS in our smartphones).  If my ideas are actually as important as I would like to believe they are, then I had better be able to make a case why somebody else should be interested in them, and a proposal is just a focusing of that discussion to a particular audience.  A good proposal isn't a sales job, it's a proposal for a mutually beneficial partnership with your potential funder, where you doing your research helps them achieve their own goals.

For a really good proposal (like, I hope, the ones we just sent in), the effort of writing the proposal is part of the preliminary research on the project.  The work of figuring out how to connect with the subject of the proposal solicitation brings up new questions and challenges and forces you to confront problems that could be avoided in prior contexts.  With a good team and a good proposal, those tensions lead to new insights even as you write, and you end up formulating a really clean plan of attack on the problems.  It exhilarating, laying out a possible future, seeing how the work all could fit together and what exciting lands it could lead to, before the realities of a project set in and we have to get engaged with all the messy details, side trips, unexpected obstacles, new phenomena, etc. that the world may soon decide to throw at us.  That's what I mean by the "new proposal smell," and it's lovely to inhale it every once in a while, and just to say together with your collaborators, when the documents are filed, "Good work everybody.  I hope we get to do it."

And none of this, of course, no matter how good your intellectual content or prose, can ensure a proposal will actually be selected for funding.  To mangle Anna Karenina, "All funded proposals are (sort of) alike, but every failed proposal may fail in a different way."  So perhaps you'll understand me when I say: the saddest thing about proposals is knowing that you may never get to do the research.

"Organizing the Aggregate" now in print

Just a short note: the book containing our review of spatial computing programming languages is now officially out and on sale, both at the publisher's website and Amazon.  It's entitled "Formal and Practical Aspects of Domain-Specific Languages: Recent Developments", and our review "Organizing the Aggregate: Languages for Spatial Computing" is Chapter 16.  Now, I don't get any cut of the sales, so it doesn't matter all that much to me whether you buy it in its elegant form in the book or just snag the content from the preprint.  But it's nice to see it in print.