The purpose of this master thesis is to enable the Robot Lisa to process complex commands and extract the necessary information in order to perform a complex task as a sequence of smaller tasks. This is intended to be achieved by the improvement of the understanding that Lisa has of her environment by adding semantics to the maps that she builds. The complex command itself will be expected to be already parsed. Therefore the way the input is processed to become a parsed command is out of the scope of this work. Maps that Lisa builds will be improved by the addition of semantic annotations that can include any kind of information that might be useful for the performance of generic tasks. This can include (but not necessarily limited to) hierarchical classifications of locations, objects and surfaces. The processing of the command in addition to some information of the environment shall trigger the performance of a sequence of actions. These actions are expected to be included in Lisa- currently implemented tasks and will rely on the currently existing modules that perform them. Nevertheless the aim of this work is not only to be able to use currently implemented tasks in a more complex sequence of actions but also make it easier to add new tasks to the complex commands that Lisa can perform.

Hybrid automata are used as standard means for the specification and analysis of dynamical systems. Several researches have approached them to formally specify reactive Multi-agent systems situated in a physical environment, where the agents react continuously to their environment. The specified systems, in turn, are formally checked with the help of existing hybrid automata verification tools. However, when dealing with multi-agent systems, two problems may be raised. The first problem is a state space problem raised due to the composition process, where the agents have to be parallel composed into an agent capturing all possible behaviors of the multi-agent system prior to the verification phase. The second problem concerns the expressiveness of verification tools when modeling and verifying certain behaviors. Therefore, this paper tackles these problems by showing how multi-agent systems, specified as hybrid automata, can be modeled and verified using constraint logic programming(CLP). In particular, a CLP framework is presented to show how the composition of multi-agent behaviors can be captured dynamically during the verification phase. This can relieve the state space complexity that may occur as a result of the composition process. Additionally, the expressiveness of the CLP model flexibly allows not only to model multi-agent systems, but also to check various properties by means of the reachability analysis. Experiments are promising to show the feasibility of our approach.

This paper describes the robot Lisa used by team homer@UniKoblenz of the University of Koblenz Landau, Germany, for the participation at the RoboCup@Home 2016 in Leipzig, Germany. A special focus is put on novel system components and the open source contributions of our team. We have released packages for object recognition, a robot face including speech synthesis, mapping and navigation, speech recognition interface via android and a GUI. The packages are available (and new packages will be released) on http://wiki.ros.org/agas-ros-pkg.

The efficiency of marketing campaigns is a precondition for business success. This paper discusses a technique to transfer advertisement content vie Bluetooth technology and collects market research information at the same time. Conventional advertisement media were enhanced by devices to automatically measure the number, distance, frequency and exposure time of passersby, making information available to evaluate both the wireless media as well as the location in general. This paper presents a study analyzing these data. A cryptographic one-way function protects privacy during data acquisition.

Distance vector routing protocols are interior gateway protocols in which every router sets up a routing table with the help of the information it receives from its neighboring routers. The routing table contains the next hops and associated distances on the shortest paths to every other router in the network. Security mechanisms implemented in distance vector routing protocols are insufficient. It is rather assumed that the environment is trustworthy. However, routers can be malicious for several reasons and manipulate routing by injecting false routing updates. Authenticity and integrity of transmitted routing updates have to be guaranteed and at the same time performance and benefits should be well-balanced. In this paper several approaches that aim at meeting the above mentioned conditions are examined and their advantages and disadvantages are compared.

In this paper, we demonstrate by means of two examples how to work with probability propagation nets (PPNs). The fiirst, which comes from the book by Peng and Reggia [1], is a small example of medical diagnosis. The second one comes from [2]. It is an example of operational risk and is to show how the evidence flow in PPNs gives hints to reduce high losses. In terms of Bayesian networks, both examples contain cycles which are resolved by the conditioning technique [3].

Dualizing marked Petri nets results in tokens for transitions (t-tokens). A marked transition can strictly not be enabled, even if there are sufficient "enabling" tokens (p-tokens) on its input places. On the other hand, t-tokens can be moved by the firing of places. This permits flows of t-tokens which describe sequences of non-events. Their benefiit to simulation is the possibility to model (and observe) causes and effects of non-events, e.g. if something is broken down.

The paper is devoted to solving a problem of the development of the website of Russian municipal policlinics and provides a selection of a set of elements which should be posted on a website. Such elements are necessary to provide citizens with correct and ergonomic e-services. The insufficient development of an infrastructure of institutions of public and municipal administration (particularly, healthcare institutions) in Russia made it necessary to analyze webresources used in different countries at different levels of providing medical services. The information resources of medical treatment facilities of the United Kingdom, of the United Statesrnof America and of the Federal Republic of Germany were researched separately for three existing economic models of healthcare. A set of criteria for the assessment of medical webresources was developed.

This paper describes artificial neural networks which are based on the adaptive resonance theory. The usage of these artificial neural networks for classification tasks is presented. The example uses is the classification of patient health from the results of general blood analysis.

This paper describes the analysis of a neural network used to predict currency exchange rates in comparison to technical analysis. The neural network structures used are a multilayer perceptron and a Volterra network.