Biologically-Inspired Robust Spatial Programming
Author(s) •
Beal, Jacob
Sussman, Gerald
Date Issued
January 18, 2005
Series/Report no.
Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory
Abstract
Inspired by the robustness and flexibility of biological systems, we are developing linguistic and programming tools to allow us to program spatial systems populated by vast numbers of unreliable components interconnected in unknown, irregular, and time-varying ways. We organize our computations around geometry, making the fact that our system is made up of discrete individuals implicit. Geometry allows us to specify requirements in terms of the behavior of the space occupied by the aggregate rather than the behavior of individuals, thereby decreasing complexity. So we describe the behavior of space explicitly, abstracting away the discrete nature of the components. As an example, we present the Amorphous Medium Language, which describes behavior in terms of homeostatic maintenance of constraints on nested regions of space.
Subjects
AI
amorphous robust biological spatial sensor networks language programming medium
Persistent DSpace Link