arXiv subjects

Mohsen Shahriari

Publications and source records attributed to Mohsen Shahriari.

3 recordsLinked to original sources

arXiv2022

The provably total recursive functions and the MRDP theorem in Basic Arithmetic and its extensions

We study Basic Arithmetic, BA introduced by W. Ruitenburg. BA is an arithmetical theory based on basic logic which is weaker than intuitionistic logic. We show that the class of the provably total recursive functions of BA is a proper sub-class of the primitive recursive functions. Three extensions of BA, called BA+U, BA_c and EBA are investigated with relation to their provably total recursive functions. It is shown that the provably total recursive functions of these three extensions of BA are exactly the primitive recursive functions. Moreover, among other things, it is shown that the well-known MRDP theorem does not hold in BA, BA+U, BA_c, but holds in EBA.

math.LO↗

arXiv2019

Investigating Cooperativity of Overlapping Community Structures in Social Networks

Many real-world networks can be modeled by networks of interacting agents. Analysis of these interactions can reveal fundamental properties from these networks. Estimating the amount of collaboration in a network corresponding to connections in a learning environment can reveal to what extent learners share their experience and knowledge with other learners. Alternatively, analyzing the network of interactions in an open source software project can manifest indicators showing the efficiency of collaborations. One central problem in such domains is the low cooperativity values of networks due to the low cooperativity values of their respective communities. So administrators should not only understand and predict the cooperativity of networks but also they need to evaluate their respective community structures. To approach this issue, in this paper, we address two domains of open source software projects and learning forums. As such, we calculate the amount of cooperativity in the corresponding networks and communities of these domains by applying several community detection algorithms. Moreover, we investigated the community properties and identified the significant properties for estimating the network and community cooperativity. Correspondingly, we identified to what extent various community detection algorithms affect the identification of significant properties and prediction of cooperativity. We also fabricated binary and regression prediction models using the community properties. Our results and constructed models can be used to infer cooperativity of community structures from their respective properties. When predicting high defective structures in networks, administrators can look for useful drives to increase the collaborations.

cs.SI↗

arXiv2019

Ranking and Cooperation in Real-World Complex Networks

People participate and activate in online social networks and thus tremendous amount of network data is generated; data regarding their interactions, interests and activities. Some people search for specific questions through online social platforms such as forums and they may receive a suitable response via experts. To categorize people as experts and to evaluate their willingness to cooperate, one can use ranking and cooperation problems from complex networks. In this paper, we investigate classical ranking algorithms besides the prisoner dilemma game to simulate cooperation and defection of agents. We compute the correlation among the node rank and node cooperativity via three strategies. The first strategy is involved in node level; however, other strategies are calculated regarding neighborhood of nodes. We find out correlations among specific ranking algorithms and cooperativtiy of nodes. Our observations may be applied to estimate the propensity of people (experts) to cooperate in future based on their ranking values.

cs.SI↗