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

1997 ◽  
Vol 44 (4) ◽  
pp. 355-361 ◽  
Author(s):  
K.R. Crounse ◽  
E.L. Fung ◽  
L.O. Chua
Keyword(s):  
Neural Network ◽  
Cellular Automata ◽  
Cellular Neural Network ◽  
Efficient Implementation ◽  
Universal Machine

Optimized cellular neural network universal machine emulation on FPGA

2007 ◽  
Author(s):  
Giovanni Egidio Pazienza ◽  
Jordi Bellana-Camanes ◽  
Jordi Riera-Babures ◽  
Xavier Vilasis-Cardona ◽  
Marco Antonio Moreno-Armendariz ◽  
...  
Keyword(s):  
Neural Network ◽  
Cellular Neural Network ◽  
Universal Machine

THE SPATIOTEMPORAL PRISONER'S DILEMMA

2000 ◽  
Vol 10 (07) ◽  
pp. 1623-1644
Author(s):  
LÁSZLÓ NEMES ◽  
LEON O. CHUA
Keyword(s):  
Neural Network ◽  
Parameter Space ◽  
Prisoner's Dilemma ◽  
Prisoner’S Dilemma ◽  
Cellular Neural Network ◽  
Natural Phenomena ◽  
Universal Machine ◽  
Individual Strategy ◽  
Spatial Prisoner’S Dilemma

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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