We continue the investigations concerning the possibility of using spiking neural P systems as a framework for solving computationally hard problems, addressing two problems which were already recently considered in this respect: Subset Sum and SAT. For both of them we provide uniform constructions of standard spiking neural P systems (i.e., not using extended rules or parallel use of rules) which solve these problems in a constant number of steps, working in a non-deterministic way. This improves known results of this type where the construction was non-uniform, and/or was using various ingredients added to the initial definition of spiking neural P systems (the SN P systems as defined initially are called here "standard"). However, in the Subset Sum case, a price to pay for this improvement is that the solution is obtained either in a time which depends on the value of the numbers involved in the problem, or by using a system whose size depends on the same values, or again by using complicated regular expressions. A uniform solution to 3- SAT is also provided, that works in constant time. © 2008 Springer Science+Business Media B.V.
Leporati, A., Mauri, G., Zandron, C., Păun, G., Pérez Jiménez, M. (2009). Uniform solutions to SAT and Subset Sum by spiking neural P systems. NATURAL COMPUTING, 8(4), 681-702 [10.1007/s11047-008-9091-y].
Uniform solutions to SAT and Subset Sum by spiking neural P systems
LEPORATI, ALBERTO OTTAVIO;MAURI, GIANCARLO;ZANDRON, CLAUDIO;
2009
Abstract
We continue the investigations concerning the possibility of using spiking neural P systems as a framework for solving computationally hard problems, addressing two problems which were already recently considered in this respect: Subset Sum and SAT. For both of them we provide uniform constructions of standard spiking neural P systems (i.e., not using extended rules or parallel use of rules) which solve these problems in a constant number of steps, working in a non-deterministic way. This improves known results of this type where the construction was non-uniform, and/or was using various ingredients added to the initial definition of spiking neural P systems (the SN P systems as defined initially are called here "standard"). However, in the Subset Sum case, a price to pay for this improvement is that the solution is obtained either in a time which depends on the value of the numbers involved in the problem, or by using a system whose size depends on the same values, or again by using complicated regular expressions. A uniform solution to 3- SAT is also provided, that works in constant time. © 2008 Springer Science+Business Media B.V.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.