You are relying on the popular-press description of the algorithm to assess its sophistication. If you would like to read it, I can send you the supplementary p

You are relying on the popular-press description of the algorithm to assess its sophistication. If you would like to read it, I can send you the supplementary pdf which explains the algorithm in detail. The algorithms do look straightforward compared to machine learning approaches, but that's a good thing! I'm guessing you're a machine learning person? I believe this approach comes more from the control theory side of automation. Simple-looking algorithms that achieve complex phenomenon is interesting. The authors also provide proofs that the algorithms will, in fact, achieve the goal. I also want to point out that they are under hardware constraints which preclude approaches which require large amounts of computation and memory. From the supplementary material: The Kilobot robot has strict limits on its available memory: 2K RAM and 32K for program memory, which includes the code for the bootloader/wireless programming, robot move- ment, and communication libraries. The full self-assembly algorithm takes approximately 27K of program memory including 241 bytes for the shape description and scale factor. The Kilobot also has limits on message size; we optimize by combining messages from the various primitives, placing all the data in a single 7 byte message. In general, I find it dangerous to make conclusions of the novelty of research from the popular press description of it.