Emerging concept of the so-called intelligent space (IS) offers means for use of mobile autonomous devices like vehicles or robots in a very broad area without necessity for these devices to own all necessary sensors. From this reason also new navigation methods are developing, which utilize IS means, with the aim to offer maybe not so accurate but first of all cheep and reliable solutions for a wide variety of devices. Our paper deals with the examination of possibility to interconnect sparsely deployed RFID tags with sonars. As signals produced by these two technologies are often affected by uncertainty and incompleteness we use fuzzy logic for their processing as well as control of the entire navigation process. For this purpose a special type of a fuzzy cognitive map was proposed. The paper describes real navigation experiments with a simple vehicle and evaluates them by selected criteria. Based on obtained results their explanations and conclusions for potential future research are sketched.

Analyses of user experience in the electronic entertainment industry currently rely on self-reporting methods, such as surveys, ratings, focus group interviews, etc. We argue that self-reporting alone carries inherent problems—mainly the misinterpretation and temporal delay during longer experiments—and therefore, should not be used as a sole metric. To tackle this problem, we propose the possibility of modeling consumer experience using psychophysiological measures and demonstrate how such models can be trained using machine learning methods. We use a machine learning approach to model user experience using real-time data produced by the autonomic nervous system and involuntary psychophysiological responses. Multiple psychophysiological measures, such as heart rate, electrodermal activity, and respiratory activity, have been used in combination with self-reporting to prepare training sets for machine learning algorithms. The training data was collected from 31 participants during hour-long experiment sessions, where they played multiple video-games. Afterwards, we trained and compared the results of four different machine learning models, out of which the best one produced ∼96% accuracy. The results suggest that psychophysiological measures can indeed be used to assess the enjoyment of digital entertainment consumers.

We propose hierarchical multi agent control system based on rule based fuzzy system for pursuit-evasion task and state a new representation of this type of game that is based on fuzzy logic. This approach enables improvement of the rule base under uncertain conditions and can process a priori inserted expert knowledge. Example application domain includes reckon and guard robots, research space probes, coordination of multiple mine sweeping devices or autonomous rescue teams.

This paper deals with application of fuzzy cognitive maps (FCM) in combination with a graph searching algorithm A for purposes of path planning for a vehicle in a traffic system with dynamic changes. In this paper a simulation of a parking problem is shown. The purpose of this paper is to show possibilities of using FCM in a dynamic environment, too.