Inconsistency and the dilemma of intuitionistic research in generative syntax

The paper is a contribution to the current debate on linguistic data and evidence. It raises two questions: (a) What kinds of inconsistency do emerge in generative syntax? (b) How are these kinds of inconsistency to be evaluated with respect to the workability of the syntactic theory at issue? As a first step, a system of paraconsistent logic is introduced which distinguishes between weak and strong inconsistency. While weak inconsistency is harmless, strong inconsistency is destructive. Second, a case study demonstrates that in generative syntax weak inconsistency may be a useful tool of problem solving. Third, two further case studies show that intuition as a data source triggers the emergence of strong inconsistency in generative syntax. Finally, this results in a methodological dilemma with far-reaching consequences

Formal Aspects of Grid Brokering

Coordination in distributed environments, like Grids, involves selecting the most appropriate services, resources or compositions to carry out the planned activities. Such functionalities appear at various levels of the infrastructure and in various means forming a blurry domain, where it is hard to see how the participating components are related and what their relevant properties are. In this paper we focus on a subset of these problems: resource brokering in Grid middleware. This paper aims at establishing a semantical model for brokering and related activities by defining brokering agents at three levels of the Grid middleware for resource, host and broker selection. The main contribution of this paper is the definition and decomposition of different brokering components in Grids by providing a formal model using Abstract State Machines

Identification of clusters of companies in stock indices via Potts super-paramagnetic transitions

The clustering of companies within a specific stock market index is studied by means of super-paramagnetic transitions of an appropriate q-state Potts model where the spins correspond to companies and the interactions are functions of the correlation coefficients determined from the time dependence of the companies' individual stock prices. The method is a generalization of the clustering algorithm by Domany et. al. to the case of anti-ferromagnetic interactions corresponding to anti-correlations. For the Dow Jones Industrial Average where no anti-correlations were observed in the investigated time period, the previous results obtained by different tools were well reproduced. For the Standard & Poor's 500, where anti-correlations occur, repulsion between stocks modify the cluster structure.Comment: 4 pages; changed conten

Transmission of cultural traits in layered ego-centric networks

Although a number of models have been developed to investigate the emergence of culture and evolutionary phases in social systems, one important aspect has not yet been sufficiently emphasized. This is the structure of the underlaying network of social relations serving as channels in transmitting cultural traits, which is expected to play a crucial role in the evolutionary processes in social systems. In this paper we contribute to the understanding of the role of the network structure by developing a layered ego-centric network structure based model, inspired by the social brain hypothesis, to study transmission of cultural traits and their evolution in social network. For this model we first find analytical results in the spirit of mean-field approximation and then to validate the results we compare them with the results of extensive numerical simulations.Comment: 10 pages, 2 figure