Efficient implementation of neighborhood logic for cellular automata via the Cellular Neural Network Universal Machine

Author(s):  
K.R. Crounse ◽  
E.L. Fung ◽  
L.O. Chua
Author(s):  
Giovanni Egidio Pazienza ◽  
Jordi Bellana-Camanes ◽  
Jordi Riera-Babures ◽  
Xavier Vilasis-Cardona ◽  
Marco Antonio Moreno-Armendariz ◽  
...  

2000 ◽  
Vol 10 (07) ◽  
pp. 1623-1644
Author(s):  
LÁSZLÓ NEMES ◽  
LEON O. CHUA

A novel platform, the cellular neural network universal machine (CNN-UM) model is proposed to simulate the spatial prisoner's dilemma (SPD) game introduced in [Nowak & May, 1992]. The application of CNN is motivated by both its high conformity with the modeled natural phenomena (analog dynamics) and its superior speed enabling the exploration of the SPD's vast parameter space. Several models are shown as examples of CNN implementation. In particular, a synchronously updated model is introduced using strategy based on best individual strategy (BIS). A new synchronous model is shown based on better average strategy (BAS). Stemming from the CNN implementation of synchronous SPD an asynchronous model has been developed employing BIS, and the survival of clusters of cooperating individuals is demonstrated. This seems to contradict the view elaborated in [Huberman & Glance 1993] claiming that the viability of cooperation is an artifact of synchronous updating in SPD.


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