Some temporal networks, most notably citation networks, are naturally represented as directed acyclic graphs (DAGs). To detect communities in DAGs, we propose a modularity for DAGs by defining an appropriate null model (i.e., randomized network) respecting the order of nodes. We implement a spectral method to approximately maximize the proposed modularity measure and test the method on citation...

We study how modularity of the human brain changes as children develop into adults. Theory suggests that modularity can enhance the response function of a networked system subject to changing external stimuli. Thus, greater cognitive performance might be achieved for more modular neural activity, and modularity might likely increase as children develop. The value of modularity calculated from f...

Despite the major role that modularity occupies in computer science all the known results on modular analysis only treat particular problems and there is no general unifying theory In this paper we provide such a general theory of modularity First we study the space of the criteria for modularity the so called modularity space and give results on its complexity Then we introduce the notion of v...

The concept of modularity is a main concern for the generation of artificially intelligent systems. Modularity is an ubiquitous organization principle found everywhere in natural and artificial complex systems (Callebaut, 2005). Evidences from biological and philosophical points of view (Caelli and Wen, 1999) (Fodor, 1983), indicate that modularity is a requisite for complex intelligent behavio...

Modularity is the fundamental aspect of modern software engineering, however many advanced modularity techniques requires prospective technologies as part of development and operation process. In this paper, we present Refinable Function, an object-oriented approach to advanced languagebased, symmetric modularity technique for the procedure. We conceptually compare Refinable Function to existin...

Clustering algorithms for large networks typically use modularity values to test which partitions of the vertex set better represent structure in the data. The modularity of a graph is the maximum modularity of a partition. We consider the modularity of two kinds of graphs. For r-regular graphs with a given number of vertices, we investigate the minimum possible modularity, the typical modulari...

Recently, Baumann et al. [2010] provided a comprehensive framework for default reasoning about actions. Alas, the approach was only defined for a very basic class of domains where all actions have mere unconditional, local effects. In this paper, we show that the framework can be substantially extended to domains with action effects that are conditional (i.e. are context-sensitive to the state ...

2. The KBMS Architecture We define and discuss an architecture for a knowledge base management system (KBMS) to support the efficient manipulation of large and diverse bodies of knowledge. The architecture has been formulated within an amalgamated language-metalanguage framework. All aspects of the system possess a logical semantics. Our emphasis is on modularity, the organization of theories a...