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| Content Provider | Springer Nature Link |
|---|---|
| Author | Sahu, Satyajit Oo, Hiroshi Ghosh, Subrata Bandyopadhyay, Anirban Fujita, Daisuke Peper, Ferdinand Isokawa, Teijiro Pati, Ranjit |
| Copyright Year | 2012 |
| Abstract | Cellular Automata (CA) have long attracted interest as abstract computation models, but only in the last few years have serious attempts started to implement them in terms of molecules. Such nano-technological innovations promise very cost-effective fabrication because of the regular structure of CA, which allows assembly through molecular self-organization. The small sizes of molecules combined with their availability in Avogadro-scale numbers promises a huge computational power, in which the massive parallelism inherent in CA can be effectively exploited. This paper discusses the molecular CA in (Bandyopadhyay et al., Nature Physics 2010) and shows novel features that have never been proposed in conventional CA models. The interaction rules in the molecular CA are found to be of a mixed variety, ranging from conventional direct-neighborhood type of rules to rules with long-distance interactions between cells. The probabilities according to which rules are applied in the molecular CA are dynamically influenced by the patterns on the cellular space. This results in extremely rich behavior, as compared to conventional models, which has the potential to be utilized for efficient configuration of patterns on the cellular space. |
| Starting Page | 311 |
| Ending Page | 321 |
| Page Count | 11 |
| File Format | |
| ISSN | 15677818 |
| Journal | Natural Computing |
| Volume Number | 11 |
| Issue Number | 2 |
| e-ISSN | 15729796 |
| Language | English |
| Publisher | Springer Netherlands |
| Publisher Date | 2012-02-25 |
| Publisher Place | Dordrecht |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Cellular Automata Molecular electronics Reconfigurability Molecular networks Processor Architectures Theory of Computation Statistical Physics, Dynamical Systems and Complexity Evolutionary Biology Artificial Intelligence (incl. Robotics) |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Science Applications |
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