Two Hands Are Better Than One (in Self-Assembly)
Scott Summers

Intrinsic Universality and the Computational Power of Self-Assembly
Damien Woods

DNA Computing by Self-Assembly

Algorithmic self-assembly uses computational thinking to design systems in which large numbers of relatively simple components autonomously combine to form complex structures or perform computations. Applying tools from computational theory to this domain has resulted in the development of a rich set of theoretical models which have provided insight into many fundamental properties, abilities, and limitations of self-assembling systems. This has also helped to form a road map for experimental work in developing artificial self-assembling systems in the laboratory. During this workshop, we will introduce several of those theoretical models and demonstrate the design of basic self-assembly systems using them. We will then survey a wide variety of results in which notions of simulation between systems within, and even across, models have been used to compare and contrast the powers of those models and the systems they contain. We will focus on the application of specific notions of simulation, including intrinsic universality, and the insights they lend into various properties of self-assembling systems.

This workshop will be designed to be accessible to those with no previous experience in self-assembly, and will start with introductions to basic definitions and models, but will finish with discussions of very recent and technical results which will also be of interest to experts in the field. Invited speakers will include Scott Summers from the University of Wisconsin-Oshkosh and Damien Woods from the California Institute of Technology, both of whom have been integral and prolific contributors to the growth of the field and especially to the simulation results discussed.