We study in detail the fitness landscape of a difficult cellular automata computational task: the majority problem. Our results show why this problem landscape is so hard to search, and we quantify the large degree of neutrality found in various ways. We show that a particular subspace of the solution space, called the "Olympus", is where good solutions concentrate, and give measures to quantitatively characterize this subspace

Verel, S., Collard, P., Tomassini, M., Vanneschi, L. (2006). Neutral fitness landscape in the cellular automata majority problem. In CELLULAR AUTOMATA, PROCEEDINGS (pp.258-267). Springer [10.1007/11861201_31].

Neutral fitness landscape in the cellular automata majority problem

VANNESCHI, LEONARDO
2006

Abstract

We study in detail the fitness landscape of a difficult cellular automata computational task: the majority problem. Our results show why this problem landscape is so hard to search, and we quantify the large degree of neutrality found in various ways. We show that a particular subspace of the solution space, called the "Olympus", is where good solutions concentrate, and give measures to quantitatively characterize this subspace
paper
neutral, fitness, landscape, cellular, automata, majority, problem
English
International Conference on Cellular Automata for Research and Industry SEP 20-23
2006
CELLULAR AUTOMATA, PROCEEDINGS
978-3-540-40929-8
2006
4173
258
267
none
Verel, S., Collard, P., Tomassini, M., Vanneschi, L. (2006). Neutral fitness landscape in the cellular automata majority problem. In CELLULAR AUTOMATA, PROCEEDINGS (pp.258-267). Springer [10.1007/11861201_31].
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/13458
Citazioni
  • Scopus 2
  • ???jsp.display-item.citation.isi??? 1
Social impact