Formal languages
Solving NP-Complete Problems With Networks of Evolutionary Processors
IWANN '01 Proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks: Connectionist Models of Neurons, Learning Processes and Artificial Intelligence-Part I
On the size complexity of hybrid networks of evolutionary processors
Theoretical Computer Science - Descriptional complexity of formal systems
Decision problems for semi-Thue systems with a few rules
Theoretical Computer Science - Insightful theory
Information Processing Letters
On the size complexity of universal accepting hybrid networks of evolutionary processors
Mathematical Structures in Computer Science
Hybrid networks of evolutionary processors
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
On the power of networks of evolutionary processors
MCU'07 Proceedings of the 5th international conference on Machines, computations, and universality
Accepting hybrid networks of evolutionary processors
DNA'04 Proceedings of the 10th international conference on DNA computing
The role of evolutionary operations in accepting hybrid networks of evolutionary processors
Information and Computation
Natural Computing: an international journal
On normal forms for networks of evolutionary processors
UC'11 Proceedings of the 10th international conference on Unconventional computation
About complete obligatory hybrid networks of evolutionary processors without substitution
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part I
Deciding networks of evolutionary processors
DLT'11 Proceedings of the 15th international conference on Developments in language theory
Complexity results for deciding Networks of Evolutionary Processors
Theoretical Computer Science
Networks of evolutionary processors: computationally complete normal forms
Natural Computing: an international journal
Hi-index | 5.23 |
A hybrid network of evolutionary processors (an HNEP) is a graph where each node is associated with an evolutionary processor (a special rewriting system), a set of words, an input filter and an output filter. Every evolutionary processor is given with a finite set of one type of point mutations (an insertion, a deletion or a substitution of a symbol) which can be applied to certain positions of a string over the domain of the set of these rewriting rules. The HNEP functions by rewriting the words that can be found at the nodes and then re-distributing the resulting strings according to a communication protocol based on a filtering mechanism. The filters are defined by certain variants of random-context conditions. HNEPs can be considered as both language generating devices (GHNEPs) and language accepting devices (AHNEPs). In this paper, by improving the previous results, we prove that any recursively enumerable language can be determined by a GHNEP and an AHNEP with 7 nodes. We also show that the families of GHNEPs and AHNEPs with 2 nodes are not computationally complete.