InfoStation-based Adaptable Provision of m Learning Services: Main Scenarios

This paper presents an adaptable InfoStation-based multi-agent system facilitating the mobile eLearning (mLearning) service provision within a University Campus. A horizontal view of the network architecture is presented. Main communications scenarios are considered by describing the detailed interaction of the system entities involved in the mLearning service provision. The mTest service is explored as a practical example. System implementation approaches are also considered.

Optimal Resource Deployment in an Infostation-Based Network

This paper considers the problem of finding an optimal deployment of information resources on an InfoStation network in order to minimize the overhead and reduce the time needed to satisfy user requests for resources. The RG-Optimization problem and an approach for its solving are presented as well.

Agent-Oriented Middleware Supporting Delivery of Mobile Elearning Services

Within project Distributed eLearning Center (DeLC) we are developing a system for distance and eLearning, which offers fixed and mobile access to electronic content and services. Mobile access is based on InfoStation architecture, which provides Bluetooth and WiFi connectivity. On InfoStation network we are developing multi-agent middleware that provides context-aware, adaptive and personalized access to the mobile services to the users. For more convenient testing and optimization of the middleware a simulation environment, called CA3 SiEnv, is being created.

Intelligent Car Parking Locator Service

This paper presents an InfoStation-based multi-agent system facilitating a Car Parking Locator service provision within a University Campus. The system network architecture is outlined, illustrating its functioning during the service provision. A detailed description of the Car Parking Locator service is given and the system entities’ interaction is described. System implementation approaches are also considered.

General Regression Neuro–Fuzzy Network for Identification of Nonstationary Plants

General Regression Neuro-Fuzzy Network, which combines the properties of conventional General Regression Neural Network and Adaptive Network-based Fuzzy Inference System is proposed in this work. This network relates to so-called “memory-based networks”, which is adjusted by one-pass learning algorithm.