Emergence-Oriented Programming

Abstract

In this paper we describe Emergence-Oriented Programming (EOP), a novel, human-centric technique to engineer swarm algorithms at a higher level of complexity than those developed with simple reactive agents. The process is iterative, building modules of behavior that can be layered to produce solutions that converge faster than reactive swarms to the desired emergent goal. The layers are modular and can be independently applied, mirroring the arbitrarily nested cognitive model proposed by Baas and Emmeche. The layers are produced by external observers recognizing and reinforcing patterns within swarms that are not visible at lower levels. Each layer builds upon the previous one leading to emergence, but the entire hierarchy can be mechanically collapsed into executable if-then rules based on robot primitives. We demonstrate portions of this technique to improve on the reactive swarm approach for solving the 4-color mapping problem.

An aspect-oriented approach for modeling self-organizing emergent structures

“…We have implemented several nondeterministic algorithms that employ agents to find the minimum coloring for both planar and non-planar graphs, with favorable results, including several fully distributed versions across a heterogeneous network [8]. Figure 1 shows a view of a simple planar graph that a set of agents are trying to solve using 4 colors.…”