A Hybrid Multi-Layered approach to Demand Responsive Transport Systems modeling
The paper discusses a multi-paradigm approach to the modeling of Demand Responsive Transport systems. It contains a brief overview of issues which appear during modeling of such systems, considers various multi-agent architectures and describes some algorithms which can be used for modeling. Also the paper provides some details about previous investigations on this topic, in particular: a centralized model based on combinatorial auctions and a multi-agent based multi-layer distributed hybrid model. The aim of the paper is working out a sound solution based on a combination of these two approaches which would utilize “system of systems” engineering approach where layered architecture would help to deal with real-time issues and increase system’s reliability and combinatorial auctions would help with global search of the optimal solution. Such combination improves the efficiency and reliability of the system.
The following topics were dealt with: human/computer interfaces; texture, depth and motor perception; neural nets; fuzzy systems; learning; product/process design; simulation; robotics; visual system cybernetics; batch processes; image compression and interpretation; AI applications; fuzzy adaptive control; decision modelling; agile manufacturing; service sector; inductive algorithms; complex systems; Petri nets; real time imaging; KBS; machine recognition; requirements engineering; inspection and shop floor control; environmental decision making; medicine; supervisory control; discrete event systems; power systems; software methods; heuristic search; vision systems; database systems; information modelling; facility design and material handling; conflict resolution; emergency management; genetic algorithms; decision making and path planning; IVHS; senses approximation; intelligent user interface; robust controllers for mechanical systems; cognitive and learning systems; command and control systems; pilot associate systems; neural net applications; real time systems; mobile robot visual processes; medical applications; utility energy systems; machine recognition; computing systems design; software engineering; military applications; data analysis; stochastic processes; guided vehicles; and stability and compensation.
Summary: There were 22 papers submitted for peer-review to the conference. Out of these, 16 papers were accepted for this volume, 7 as regular papers and 9 as short papers.
Nested Petri nets is an extension of Petri net formalism with net tokens for modelling multi-agent distributed systems with complex structure. While having a number of interesting properties, NP-nets have been lacking tool support. In this paper we present the NPNtool toolset for NP-nets which can be used to edit NP-nets models and check liveness in a compositional way. An algorithm to check m-bisimiliarity needed for compositional checking of liveness has been developed. Experimental results of the toolset usage for modelling and checking liveness of classical dinning philosophers problem are provided.
There have been implemented engineering and development of multi-agent recommender system «EZSurf» that performs analysis of interests and provides recommendations for the social network «VKontakte» users based on the data from profile of particular user. During the work process different methods and technological solutions have been analyzed with examination of their advantages and disadvantages. Besides of that the comparative analysis of analogous products has been held where the most similar is Russian start-up service - Surfingbird. Based on this analysis the decision of recommender system implementation and integration has been accepted. The feature of this system is that it uses social network “VKontakte” profile for user’s data collection and API of third-party services (LastFM, TheMovieDB) for an extraction of information about similar objects. Such an approach contributes into optimization of recommender system, because it does not require creation of its own object classification system and objects database. The functionality of multi-agent system was separated between three agents. First agent (Collector) collects user data from “VKontakte” profile using VK API. Second agent (Analyzer) collects similar objects from databases of thitd-party services (LastFM, TheMovieDB) that will be the criteria for further search of recommendatory content. For search and selection of information an agent (Recommender) that works as web-crawler has been implemented. System «EZSurf» can be exploited by the users of social network “VKontakte” in everyday life for time economy on web-surfing process. At the same time they will get recommendations on content that are filtered depending on preferences of every particular user.
Resource-driven automata (RDA) are finite automata, sitting in the nodes of a finite system net and asynchronously consuming/producing shared resources through input/output system ports (arcs of the system net). RDAs themselves may be resources for each other, thus allowing the highly flexible structure of the model. It was proved earlier, that RDA-nets are expressively equivalent to Petri nets. In this paper the new formalism of cellular RDAs is introduced. Cellular RDAs are RDA-nets with an infinite regularly structured system net. We build a hierarchy of cellular RDA classes on the basis of restrictions on the underlying grid. The expressive power of several major classes of 1-dimensional grids is studied.
The article presents the development of the ontology for a multi-agent subsystem analysing user posts in social networks in order to identify security threats to society. The testing of multi-agent subsystem using the developed ontology is described.