PX systems = P systems + X machines

The paper is a survey of the main features of P systems, X machines and of a new computational device called PX system. The sequential and the parallel PX systems are presented. Results reflecting the computational power of these models and their effectiveness in solving NP-complete problems are briefly mentioned.     

Spiking neural P systems: An improved normal form

Spiking neural P systems (in short, SN P systems) are computing devices based on the way the neurons communicate through electrical impulses (spikes). These systems involve various ingredients; among them, we mention forgetting rules and the delay in firing rules. However, it is known that the universality can be obtained without using these two features. In this paper we improve this result in two respects: (i) each neuron contains at most two rules (which is optimal for systems used in the generative mode), and (ii) the rules in the neurons using two rules have the same regular expression which controls their firing. This result answers a problem left open in the literature, and, in this context, an incompleteness in some previous proofs related to the elimination of forgetting rules is removed. Moreover, this result shows a somewhat surprising uniformity of the neurons in the SN P systems able to simulate Turing machines, which is both of a theoretical interest and it seems to correspond to a biological reality. When a bound is imposed on the number of spikes present in a neuron at any step of a computation (such SN P systems are called finite), two surprising results are obtained. First, a characterization of finite sets of numbers is obtained in the generative case (this contrasts the case of other classes of SN P systems, where characterizations of semilinear sets of numbers are obtained for finite SN P systems). Second, the accepting case is strictly more powerful than the generative one: all finite sets and also certain arithmetical progressions can be accepted. A precise characterization of the power of accepting finite SN P systems without forgetting rules and delay remains to be found.     

P Systems with Mobile Membranes

P systems with active membranes are among the central ones in membrane computing, and they were shown to be both computationally universal (able to simulate Turing machines) and computationally efficient (able to solve hard problems in polynomial time). However, in all cases, these results were obtained by making use of several powerful features, such as membrane polarization, label changing, division of non-elementary membranes, priorities, or cooperative rules. This paper contributes to the research effort of introducing a class of P systems with active membranes having none of the features mentioned above, but still preserving the power and the efficiency. The additional feature we consider instead are the operations of endocytosis and exocytosis: moving a membrane inside a neighboring membrane, or outside the membrane where it is placed. We investigate the power and the efficiency of these systems (also using membrane division) by first proving that they can simulate (with a linear slowdown and without introducing non-determinism) rewriting P systems with 2-replication, for which the universality and the possibility of solving NP-complete problems in polynomial time are known. In this way, the universality and efficiency are also obtained for our systems. We also give a direct and simple proof for the universality result – without using division rules (the proof uses nine membranes, but we do not know whether this number can be decreased).     

非结构化P2P系统Overlay优化技术综述

非结构化P2P Overlay网络的结构松散, 网络中资源的分布没有明确的限制, 这使得非结构化P2P Overlay网络中的资源搜索在很大程度上依赖于通信开销巨大的泛洪法, 因而非结构化P2P系统在伸缩性, 可用性等方面, 存在明显的不足. 非结构化P2POverlay网络的上述特点决定了非结构化P2P Overlay优化技术的重要性. 本文分四大类别, 对非结构化P2P Overlay优化技术进行了介绍, 分析比较了各类方法的优劣以及它们的适用场合, 并在此基础上对未来工作进行了展望.     

基于DHT的P2P系统的负载均衡算法

在基于DHT的结构化P2P系统中,DHT的使用以及节点处理能力的不同导致系统中节点的负载不均衡.现有的负载均衡算法存在两个不足：①负载的转移没有考虑节点之间的链路延迟;②算法依赖于系统中固定位置的某些节点.提出了分布式负载均衡算法：每个节点周期性的收集系统局部负载信息,然后选择链路延迟较小的节点进行负载转移.算法依赖于系统中的所有节点,解决了单点失败问题.同时,负载的转移是在链路延迟较小的节点之间进行的.仿真实验表明,①对于各种系统利用率,该算法都可以获得理想的负载均衡效果;②算法可以使负载转移开销减少45%以上.     

Adaptive fuzzy spiking neural P systems for fuzzy inference and learning

Fuzzy spiking neural P systems (in short, FSN P systems) are a novel class of distributed parallel computing models, which can model fuzzy production rules and apply their dynamic firing mechanism to achieve fuzzy reasoning. However, these systems lack adaptive/learning ability. Addressing this problem, a class of FSN P systems are proposed by introducing some new features, called adaptive fuzzy spiking neural P systems (in short, AFSN P systems). AFSN P systems not only can model weighted fuzzy production rules in fuzzy knowledge base but also can perform dynamically fuzzy reasoning. It is important to note that AFSN P systems have learning ability like neural networks. Based on neuron's firing mechanisms, a fuzzy reasoning algorithm and a learning algorithm are developed. Moreover, an example is included to illustrate the learning ability of AFSN P systems.     

P2P系统中一种基于声誉的混合抗污染机制

提出一种新的基于节点声誉和目标声誉的混合抗污染机制。该机制由投票节点的声誉决定选定的目标文件的声誉。节点声誉通过引入严厉的惩罚策略及投票激励机制,有效孤立了污染者,刺激了用户对文件污染的警觉度,阻止污染的进一步扩散。仿真结果表明,与目标声誉系统相比,该机制收敛更快,抗污染性能更好。     

Spiking neural P systems with extended rules: universality and languages

We consider spiking neural P systems with rules allowed to introduce zero, one, or more spikes at the same time. The motivation comes both from constructing small universal systems and from generating strings; previous results from these areas are briefly recalled. Then, the computing power of the obtained systems is investigated, when considering them as number generating and as language generating devices. In the first case, a simpler proof of universality is obtained, while in the latter case we find characterizations of finite and recursively enumerable languages (without using any squeezing mechanism, as it was necessary in the case of standard rules). The relationships with regular languages are also investigated.     

模糊近似空间上的粗糙模糊集的公理系统

粗糙集理论是近年来发展起来的一种有效的处理不精确、不确定、含糊信息的理论,在机器学习及数据挖掘等领域获得了成功的应用．粗糙集的公理系统是粗糙集理论与应用的基础．粗糙模糊集是粗糙集理论的自然的有意义的推广．作者研究了模糊近似空间上的粗糙模糊集的公理系统,用三条简洁的相互独立的公理完全刻划了模糊近似空间上的粗糙模糊集,同时还把作者给出的公理系统与粗糙集的公理系统做了对比,指出了两者的区别．     

带反脉冲的同质脉冲神经膜系统

脉冲神经膜系统是一种膜系统中吸收了脉冲神经网络特点的新型生物计算装置,具有强大的计算能力.带反脉冲的同质脉冲神经膜系统是使用了两种对象(称为脉冲和反脉冲)、且其中每个神经元具有相同规则集合的一种脉冲神经膜系统的变体.本文研究了无延迟规则和突触权值情况下的带反脉冲同质脉冲神经膜系统的计算通用性问题,证明了这种P系统无论是工作在产生模式,还是接收模式下都是计算通用的.本文解答了曾湘祥等人提出的关于是否存在无延迟规则的同质脉冲神经膜系统和如何移除突触权值的两个公开问题.     

P systems with energy accounting ∗

We consider P systems where each evolution rule “Produces” or “Consumes” some quantity of energy, in amounts which are expressed as integer numbers. In each moment and in each membrane the total energy involved in an evolution step should be positive, but if “Soo much” energy is present in a membrane, then the membrane will be destroyed (dissolved). We show that this feature is rather powerful. In the case of multisets of symbol-objects we find that systems with two membranes and arbitrary energy associated with rules, or with arbitrarily many membranes and a bounded energy associated with rules characterize the recursively enumerable sets of vectors of natural numbers (catalysts and priorities are used). In the case of string-objects we have only proved that the recursively enumerable languages can be generated by systems with arbitrarily many membranes and bounded energy; when bounding the number of membranes and leaving free the quantity of energy associated with each rule we have only generated all matrix languages. Several research topics are also pointed out.     

PATCOM:基于分割树的无结构P2P系统一致性维护方法

无结构P2P技术逐渐被应用在新型的协同计算系统中.这些新型业务支持数据的动态更新,不仅要求副本数据的强一致性,而且要求更新数据的快速传播.高效的一致性维护方法是保证新业务顺利开展的基础.在比较分析现有的P2P系统一致性维护方法的基础上,针对无结构P2P系统,提出了一种基于分割树的一致性维护方法--PATCOM.PATCOM使用Chord协议作为组管理协议,通过不断分割由副本节点组成的Chord环,动态地建立更新消息传播树(Update Message Propagation Tree,UMPT).论文进一步从理论上分析了UMPT的平均高度、PATCOM的性能、容错能力以及算法开销,并和基于Gossip的一致性维护方法进行了比较.理论分析和仿真实验结果表明:PATCOM不仅能够快速地维护P2P系统的强一致性,而且产生的冗余更新消息少.     

一种基于模糊理论的P2P系统动态可信模型*

针对现有的P2P系统信任模型在信任度的计算上过于复杂的问题,提出了一种基于模糊理论的动态可信度等级模型DTD(dynamic trust degree model)。该模型在通过对信任度的传递进行细粒度的分析,设计了一种计算对信任值传递的计算方法,并结合对直接信任度和推荐信任的多级别综合评价而获得最终的信任度。模型将P2P系统中信任的计算转换为了一种可计算的表达式,简化了信任的计算过程,使信任的计算变得更加灵活。     

Compositional semantics and behavioral equivalences for P Systems

The aim of the paper is to give a compositional semantics in the style of the Structural Operational Semantics (SOS) and to study behavioral equivalence notions for P Systems. Firstly, we consider P Systems with maximal parallelism and without priorities. We define a process algebra, called P Algebra, whose terms model membranes, we equip the algebra with a Labeled Transition System (LTS) obtained through SOS transition rules, and we study how some equivalence notions defined over the LTS model apply in our case. Then, we consider P Systems with priorities and extend the introduced framework to deal with them. We prove that our compositional semantics reflects correctly maximal parallelism and priorities.     

Array-rewriting P systems

We consider array languages (sets of picturesconsisting of symbols placed in the lattice points of the 2D grid) and thepossibility to handle them with P systems. After proving binary normal formsfor array matrix grammars (which, even in the case when no appearance checking isused, are known to generate the array languages of arbitrary array grammars), weprove that the P systems with context-free rules (with three membranes and no control on the communication or the use of rules) are computationally universal, able togenerate all computable array languages. Some open problems are also formulated.     

基于模糊理论的P2P网络主观信任模型-FSTM

由于P2P网络的开放、匿名等特点,节点间的信任关系往往很难通过客观的信任机制建立.本文引入模糊理论的方法对信任进行度量,通过改进Einstein算子来解决信任向量的传递和合并问题,并把算子用于求全局信任关系模糊矩阵的传递闭包,结合分布式哈希表的机制来存储全局信誉值,较好的解决了信任的传播问题.仿真实验表明该模型能有效的提高P2P网络交互成功率,同时系统开销相对较小.     

A software tool for verification of Spiking Neural P Systems

The formal verification of a Spiking Neural P System (SN P Systems, for short) designed for solving a given problem is usually a hard task. Basically, the verification process consists of the search of invariant formulae such that, once proved their validity, show the right answer to the problem. Even though there does not exist a general methodology for verifying SN P Systems, in (Păun et al., Int J Found Comput Sci 17(4):975–1002, 2006) a new tool based on the transition diagram of the P system has been developed for helping the researcher in the search of invariant formulae. In this paper we show a software tool which allows to generate the transition diagram of an SN P System in an automatic way, so it can be considered as an assistant for the formal verification of such computational devices.

基于非结构化P2P的副本技术的研究和应用

副本技术是P2P网络中常用的一种数据管理机制,在P2P网络中,由于节点的高度动态性,致使副本管理也必须具有动态性,副本管理是一项极具研究价值的课题。如何利用副本技术来提高非结构化P2P网络的资源搜索效率仍是目前尚未有效解决的难点之一。对非结构化P2P网络中广泛应用的Gossip协议和副本管理策略进行了探索和研究,运用模糊理论提出一种副本存储节点的选择策略。通过模拟实验,对相关数据进行分析,证明该项研究能有效提高对等网络中资源搜索的效率。     

Unexpected universality results for three classes of P systems with symport/antiport

Symport and antiport are biological ways of transporting molecules through membranesin ``collaborating' pairs; in the case of symport the two molecules pass in the same direction, in the case of antiport the two molecules pass in opposite directions. Here we first survey the results about the computing power of membrane systems (P systems) using only symport/antiport rules (hence these systems compute by communication only), then we consider a recently introduced, way of defining the result of a computation in a membrane system: looking for the trace of certain objects in their movement through membranes. Rather unexpected, in this way we get characterizations of recursively enumerable languages by means of membrane systems with symport/antiport which work with multisets of objects (note the qualitative difference between the data structure used by computations – multisets: no ordering– and the data structure of the output – strings: linear ordering). A similar remark holds true for the case of analysing P systems, which work in an automata-like manner: the sequence of certain distinguished objects taken from the environment during acomputation is the string recognized by the computation. We also survey universality results from this area, with sketched proofs. Some open problems are also formulated. This revised version was published online in June 2006 with corrections to the Cover Date.     

Hybrid artificial intelligence approach to urban planning

Knowledge-based modeling and implementation of the various urban planning processes represent an intensive research area. This paper presents a hybrid artificial intelligence system using a knowledge-based approach, neural networks and fuzzy logic that automates the decision-making process in urban planning. The system is used for developing urban development alternatives based on real-world data. Results show that, by integrating knowledge-based systems, artificial neural networks and fuzzy systems, the system achieves improvements in the implementation of each respective system as well as an increase in the breadth of functionality within the application. With this approach, the best of three technologies can be compiled together to solve complex urban problems. We discuss the structure of the combined technologies, as well as providing examples of its application in the field of urban development.