Deliberative reasoning is widely used in various fields of human activity. In the modern information society, the use of methods of deliberative argumentation is associated with the development and use of appropriate application software, which is intended for visualization and modeling of intellectual activity to solve various types of practical problems, as well as argumentation. At the same time, various software designed for modeling and representation of argumentation explicitly or implicitly contains its conceptual grounds for argumentation. In this study, based on the identification of software intended for the simulation of deliberative reasoning, analysis of its purpose and main functions, the conceptual foundations of their functioning are determined, which is the initial stage for the formulation of a body of criteria for evaluating this software and its subsequent classification. The authors propose two preliminary independent classifications based on conceptual grounds, which are significant characteristics for the classification of the corresponding software.
We study synchronization aspects in parallel discrete event simulation (PDES) algorithms. Our analysis is based on the recently introduced model of virtual times evolution in an optimistic synchronization algorithm. This model connects synchronization aspects with the properties of the profile of the local virtual times. The main parameter of the model is a “growth rate” q = 1/(1 + b), where b is a mean rollback length. We measure the average utilization of events and the desynchronization between logical processes as functions of the parameter q. We found that there is a phase transition between an “active phase”, i.e. when the utilization of the average processing time is finite, and an “absorbing state” with zero utilization, vanishing at a critical point qc ≈ 0.136. The average desynchronization degree (i.e. the vari- ance of local virtual times) grows with the parameter q. We also investi- gate the influence of the sparse distant communications between logical processes and found that they do not change drastically the synchronization properties in the optimistic synchronization algorithm, which is the sharp contrast with the conservative algorithm . Finally, we compare our results with the existing case-study simulations.
The International conference “Linguistic Forum 2020: Language and Artificial Intelligence” took place in 2020 on November 12-14 in Moscow, Russia. The conference is organized by the Institute of Linguistics, Russian Academy of Sciences. This conference is part of a series of annual forums initiated by the Institute of Linguistics RAS in 2019. The aim of the 2020 forum is to foster dialogue among researchers working at the interface of linguistics and artificial intelligence including those engaged in computational linguistics and natural language processing. Developments in AI have been responsible for recent advances in natural language generation and comprehension; they have also expanded the boundaries of these technologies’ applicability. Neural networks and dense embeddings have replaced models based on feature engineering and traditional discrete categories of linguistic analysis. As a result, the boundary between fundamental and applied linguistic research is being eroded. Empirical linguistics is taking on board these new technologies, in part, to enable better modelling of language and documentation of data. AI is also increasingly becoming a part of the everyday life of language users. Can fundamental linguistics currently offer technologically viable ideas or methods? These and similar conceptual and methodological problems were the focus of the forum.
AIST is a scientific conference on Analysis of Images, Social Networks, and Texts. The conference is intended for computer scientists and practitioners whose research interests involve Internet mathematics and other related fields of data science. Similar to the previous year, the conference will be focused on applications of data mining and machine learning techniques to various problem domains: image processing, analysis of social networks, and natural language processing. We hope that the participants will benefit from the interdisciplinary nature of the conference and exchange experience.