Exploiting the selfish gene algorithm for evolving cellular automata

Abstract

This paper shows an application in the field of Electronic CAD of the Selfish Gene algorithm, an evolutionary algorithm based on a recent interpretation of the Darwinian theory. Testing is a key issue in the design and production of digital circuits and the adoption of Built-In Self-Test (BIST) techniques is increasingly popular. In this paper, the Selfish Gene algorithm is adopted for determining the logic for a BIST architecture based on Cellular Automata (CA). A Genetic Algorithm has already been proposed for identifying good BIST architectures based on CA. However, adopting 2-bit cells, such method introduced a significant area overhead. Thanks to the adoption of the new and more powerful search engine, we were able to identify simpler BIST structures with a lower area overhead, but still able to obtain the same fault coverage.

Sgmit

“…Only genes can survive in the evolu-tion process. Fulvio Corno and his cooperators followed this idea and proposed a new evolutionary optimization strategy called Selfish Gene Theory (SG) [8,7,9].…”

Evolving cellular automata for location management in mobile computing networks

“…In this paper, we propose to develop a parallel and distributed reporting cells planning algorithm based on a recently emerging and promising technique of combining evolutionary computation and cellular automata (CA) to create an "evolving" cellular automata system. Recent results suggest that highly parallel and distributed algorithms can "evolve" using such a hybrid system, solving complex problems ranging from classification to multiprocessor scheduling [2], [5], [12], [13], [14], [21], [23].…”