Agents for educational games and simulations

This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications

Modeling IoT Smart Home Network

The purpose of the article is to present the process of modeling the IoT smart home (SH) network, which combines both user needs and efficiency requirements. The use of Alibaba cloud platform, which reduces complexity and development time, reduces costs, was justified in the project of building the IoT SH network. The structure of this platform is given, its main components are considered and an algorithm for its configuration is given. MQTT is used as an access protocol in the IoT SH network to achieve fast and reliable data transmission. Open source code, reliability, simplicity and other characteristics justify the choice of this data transfer protocol. Modeling of the network IoT SH is based on the knowledge gained in the process of practical implementation. First, the online problems of the system are tested, after the system is able to work after modification and debugging of programs, a street lamp is used as an example to create an instance of an IoT SH network on a cloud platform. The process of creating an example of an IoT SH network is described in detail in steps, in which data from a street lamp is transmitted to a cloud platform, processed there, and then displayed on a mobile device. A mobile phone was used to implement two-way interaction, simulate the sensor of the IoT SH network and display the results. The algorithms for configuring the platform, modeling the sensor and creating an object model of the device of the IoT SH network are given. For some modern control systems, this system is compatible and suitable for a larger number of cases, which contributes to the development of intelligent control in the IoT network.The purpose of the article is to present the process of modeling the IoT smart home (SH) network, which combines both user needs and efficiency requirements. The use of Alibaba cloud platform, which reduces complexity and development time, reduces costs, was justified in the project of building the IoT SH network. The structure of this platform is given, its main components are considered and an algorithm for its configuration is given. MQTT is used as an access protocol in the IoT SH network to achieve fast and reliable data transmission. Open source code, reliability, simplicity and other characteristics justify the choice of this data transfer protocol. Modeling of the network IoT SH is based on the knowledge gained in the process of practical implementation. First, the online problems of the system are tested, after the system is able to work after modification and debugging of programs, a street lamp is used as an example to create an instance of an IoT SH network on a cloud platform. The process of creating an example of an IoT SH network is described in detail in steps, in which data from a street lamp is transmitted to a cloud platform, processed there, and then displayed on a mobile device. A mobile phone was used to implement two-way interaction, simulate the sensor of the IoT SH network and display the results. The algorithms for configuring the platform, modeling the sensor and creating an object model of the device of the IoT SH network are given. For some modern control systems, this system is compatible and suitable for a larger number of cases, which contributes to the development of intelligent control in the IoT network

Probabilistic Human-Robot Information Fusion

This thesis is concerned with combining the perceptual abilities of mobile robots and human operators to execute tasks cooperatively. It is generally agreed that a synergy of human and robotic skills offers an opportunity to enhance the capabilities of today’s robotic systems, while also increasing their robustness and reliability. Systems which incorporate both human and robotic information sources have the potential to build complex world models, essential for both automated and human decision making. In this work, humans and robots are regarded as equal team members who interact and communicate on a peer-to-peer basis. Human-robot communication is addressed using probabilistic representations common in robotics. While communication can in general be bidirectional, this work focuses primarily on human-to-robot information flow. More specifically, the approach advocated in this thesis is to let robots fuse their sensor observations with observations obtained from human operators. While robotic perception is well-suited for lower level world descriptions such as geometric properties, humans are able to contribute perceptual information on higher abstraction levels. Human input is translated into the machine representation via Human Sensor Models. A common mathematical framework for humans and robots reinforces the notion of true peer-to-peer interaction. Human-robot information fusion is demonstrated in two application domains: (1) scalable information gathering, and (2) cooperative decision making. Scalable information gathering is experimentally demonstrated on a system comprised of a ground vehicle, an unmanned air vehicle, and two human operators in a natural environment. Information from humans and robots was fused in a fully decentralised manner to build a shared environment representation on multiple abstraction levels. Results are presented in the form of information exchange patterns, qualitatively demonstrating the benefits of human-robot information fusion. The second application domain adds decision making to the human-robot task. Rational decisions are made based on the robots’ current beliefs which are generated by fusing human and robotic observations. Since humans are considered a valuable resource in this context, operators are only queried for input when the expected benefit of an observation exceeds the cost of obtaining it. The system can be seen as adjusting its autonomy at run-time based on the uncertainty in the robots’ beliefs. A navigation task is used to demonstrate the adjustable autonomy system experimentally. Results from two experiments are reported: a quantitative evaluation of human-robot team effectiveness, and a user study to compare the system to classical teleoperation. Results show the superiority of the system with respect to performance, operator workload, and usability

TRÓJWYMIAROWA WIZUALIZACJA STRUKTUR PRZEPŁYWÓW DWUFAZOWYCH PRZY UŻYCIU ELEKTRYCZNEJ TOMOGRAFII POJEMNOŚCIOWEJ – ALGORYTMY I OPROGRAMOWANIE

This paper presents the software for comprehensive processing and visualization of 2D and 3D electrical tomography data. The system name as TomoKIS Studio has been developed in the frame of DENIDIA international research project and has been improved in the frame of Polish Ministry of Science and Higher Education Project no 4664/B/T02/2010/38. This software is worldwide unique because it simultaneously integrates the process of tomographic data acquisition, numerical FEM modeling and tomographic images reconstruction. The software can be adapted to specific industrial applications, particularly to monitoring and diagnosis of two-phase flows. The software architecture is composed of independent modules. Their combination offers calibration, configuration and full-duplex communication with any tomographic acquisition system with known and open communication protocol. The other major features are: online data acquisition and processing, online and offline 2D/3D images linear and nonlinear reconstruction and visualization as well as raw data and tomograms processing. Another important ability is 2D/3D ECT sensor construction using FEM modeling. The presented software is supported with the multi-core GPU technology and parallel computing using Nvidia CUDA technology.W artykule autorzy przedstawiają środowisko komputerowe do kompleksowego przetwarzania i wizualizacji tomograficznych danych pomiarowych. Oprogramowanie  TomoKIS Studio powstało w Instytucie Informatyki Stosowanej PŁ w ramach projektu DENIDIA i zostało rozwinięte w ramach projektu MNiSW nr 4664/B/T02/2010/38. Zbudowane oprogramowanie jest unikalne w skali światowej, gdyż integruje w sobie proces pozyskiwania danych pomiarowych, modelowanie numeryczne oraz proces konstruowania obrazów tomograficznych, z możliwością adaptacji dla różnych aplikacji przemysłowych, w szczególności dla potrzeb monitorowania i diagnostyki przepływów dwufazowych gaz-ciecz. Architektura aplikacji oparta jest na zestawie niezależnych modułów, które pozwalają na w pełni dwukierunkową komunikacją, konfigurację oraz kalibrację dowolnego urządzenia tomografii elektrycznej z otwartym protokołem pomiarowym, akwizycję i przetwarzanie danych pomiarowych on-line, liniową oraz nieliniową rekonstrukcję obrazów 2D i 3D w czasie rzeczywistym, a także wizualizację surowych danych pomiarowych i tomogramów. Istotnym elementem systemu jest moduł numerycznego modelowania czujników pojemnościowych wykorzystujący metodę elementów skończonych, oparty na autorskich algorytmach generowania siatek MES komputerowych modeli czujników pojemnościowych. Architektura prezentowanego systemu została zaprojektowana przy użyciu obliczeń równoległych na procesorach graficznych, z wykorzystaniem technologii Nvidia CUDA

A framework to develop adaptive multimodal dialog systems for Android-based mobile devices

Proceedings of: 9th International Conference (HAIS 2014), Salamanca, Spain, June 11-13, 2014Mobile devices programming has emerged as a new trend in software development. The main developers of operating systems for such devices have provided APIs for developers to implement their own applications, including different solutions for developing voice control. Android, the most popular alternative among developers, offers libraries to build interfaces including different resources for graphical layouts as well as speech recognition and text-to-speech synthesis. Despite the usefulness of such classes, there are no strategies defined for multimodal interface development for Android systems, and developers create ad-hoc solutions that make apps costly to implement and difficult to compare and maintain. In this paper we propose a framework to facilitate the software engineering life cycle for multimodal interfaces in Android. Our proposal integrates the facilities of the Android API in a modular architecture that emphasizes interaction management and context-awareness to build sophisticated, robust and maintainable applications.This work was supported in part by Projects MINECO TEC2012-37832-C02-01, CICYT TEC2011-28626-C02-02, CAM CONTEXTS (S2009/TIC-1485)

Model-based reasoning for power system management using KATE and the SSM/PMAD

The overall goal of this research effort has been the development of a software system which automates tasks related to monitoring and controlling electrical power distribution in spacecraft electrical power systems. The resulting software system is called the Intelligent Power Controller (IPC). The specific tasks performed by the IPC include continuous monitoring of the flow of power from a source to a set of loads, fast detection of anomalous behavior indicating a fault to one of the components of the distribution systems, generation of diagnosis (explanation) of anomalous behavior, isolation of faulty object from remainder of system, and maintenance of flow of power to critical loads and systems (e.g. life-support) despite fault conditions being present (recovery). The IPC system has evolved out of KATE (Knowledge-based Autonomous Test Engineer), developed at NASA-KSC. KATE consists of a set of software tools for developing and applying structure and behavior models to monitoring, diagnostic, and control applications

Increasingly automated procedure acquisition in dynamic systems

Procedures are widely used by operators for controlling complex dynamic systems. Currently, most development of such procedures is done manually, consuming a large amount of paper, time, and manpower in the process. While automated knowledge acquisition is an active field of research, not much attention has been paid to the problem of computer-assisted acquisition and refinement of complex procedures for dynamic systems. The Procedure Acquisition for Reactive Control Assistant (PARC), which is designed to assist users in more systematically and automatically encoding and refining complex procedures. PARC is able to elicit knowledge interactively from the user during operation of the dynamic system. We categorize procedure refinement into two stages: diagnosis - diagnose the failure and choose a repair - and repair - plan and perform the repair. The basic approach taken in PARC is to assist the user in all steps of this process by providing increased levels of assistance with layered tools. We illustrate the operation of PARC in refining procedures for the control of a robot arm

An Adaptive User Interface in Healthcare

AbstractHealthcare is a broad subject with many different challenges, yet it is important and relatable to everyone. The aging Baby Boomer generation is an important healthcare issue today. In Canada, and many other developed nations, the number of citizens reaching the age of retirement and seniority is growing faster than the rate of citizens working and providing health related services. As people age they tend to require more frequent checkups and health services, ultimately putting a bigger resource drain on healthcare infrastructure. New advancements in Computer Science and Engineering are allowing the development of next generation applications with the purpose of providing healthcare services in a cost effective and efficient way. This paper proposes a multi-agent system for tracking and monitoring health data for patients. Furthermore, agents within the system use reinforcement learning techniques to build an adaptive user interface for each human user. The actions and behaviour of users are monitored and used to modify their respective user interface over time. To demonstrate the feasibility of the architecture, two scenarios are provided. We conclude with several possible future directions for this research