The connection machine
Handbook of Formal Languages
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Networks of Parallel Language Processors
New Trends in Formal Languages - Control, Cooperation, and Combinatorics (to Jürgen Dassow on the occasion of his 50th birthday)
On the size complexity of universal accepting hybrid networks of evolutionary processors
Mathematical Structures in Computer Science
On the size of computationally complete hybrid networks of evolutionary processors
Theoretical Computer Science
Filter Position in Networks of Evolutionary Processors Does Not Matter: A Direct Proof
DNA Computing and Molecular Programming
Theory of Computing Systems
Small universal accepting hybrid networks of evolutionary processors
Acta Informatica
On normal forms for networks of evolutionary processors
UC'11 Proceedings of the 10th international conference on Unconventional computation
Deciding networks of evolutionary processors
DLT'11 Proceedings of the 15th international conference on Developments in language theory
Deciding according to the shortest computations
CiE'11 Proceedings of the 7th conference on Models of computation in context: computability in Europe
Accepting hybrid networks of evolutionary processors
DNA'04 Proceedings of the 10th international conference on DNA computing
| Hi-index | 5.23 |
The Accepting Networks of Evolutionary Processors (ANEPs for short) are bio-inspired computational models which were introduced and thoroughly studied in the last decade. In this paper we propose a method of using ANEPs as deciding devices. More precisely, we define a new halting condition for this model, which seems more coherent with the rest of the theory than the previous such definitions, and show that all the computability related results reported so far remain valid in the new framework. Further, we are able to show a direct and efficient simulation of an arbitrary ANEP by an ANEP having a complete underlying graph; as a consequence of this result, we conclude that the efficiency of deciding a language by ANEPs is not influenced by the network's topology. Finally, focusing on the computational complexity of ANEP-based computations, we obtain a surprising characterisation of P^N^P^[^l^o^g^] as the class of languages that can be decided in polynomial time by such networks.