The ARNN model relativises P = NP and P ≠ NP

被引：2
|
作者：
Costa, Jose Felix [1 ,2 ]
Leong, Raimundo [1 ]
机构：
[1] Univ Tecn Lisboa, Inst Super Tecn, Dept Math, P-1096 Lisbon, Portugal
[2] Univ Lisbon, Ctr Matemat & Aplicacoes Fundamentais Complex Int, P-1699 Lisbon, Portugal
来源：
THEORETICAL COMPUTER SCIENCE | 2013年 / 499卷
关键词：
Analog recurrent neural nets (ARNN model); Non-deterministic neural nets; Dynamical systems; Cost of an oracle; Simulation of a real weighted neural net by an oracle Turing machine; Positive relativisation of P = NP; PHYSICAL EXPERIMENTS; COMPUTATION; ORACLES;
D O I：
10.1016/j.tcs.2013.05.022
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In this paper we prove that the relations P = NP and P not equal NP relativise to the deterministic/non-deterministic artificial recurrent neural net (ARNN) with real weights (informally considered as oracles in Martin Davis (2006) [10,11 1]). Although, in the nineties, a dozen of papers were written on the ARNN model, some introducing computation via neural nets with real weights and some introducing non-deterministic and stochastic neural nets, it seems that no one noticed such a relativisation, which makes the ARNN an interesting but restricted model of computation. (C) 2013 Elsevier B.V. All rights reserved.
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页码：2 / 22
页数：21
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