Combinatorial Optimization of Sensing for Rule-Based Planar Distributed Assembly

We describe a model for planar distributed assembly, in which agents move randomly and independently on a two-dimensional grid, joining square blocks together to form a desired target structure. The agents have limited capabilities, including local sensing and rule-based reactive control only, and operate without centralized coordination. We define the spatiotemporal constraints necessary for the ordered assembly of a structure and give a procedure for encoding these constraints in a rule set, such that production of the desired structure is guaranteed. Our main contribution is a stochastic optimization algorithm which is able to significantly reduce the number of environmental features that an agent must recognize to build a structure. Experiments show that our optimization algorithm outperforms existing techniques