SEARCH FILTERS
Time filter
Source Type

Skulimowski A.M.J.,AGH University of Science and Technology | Skulimowski A.M.J.,Business Center Poland
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2017

This paper presents an overview of the cognitive aspects of content recommendation process in large heterogeneous knowledge repositories and their applications to design algorithms of incremental learning of users’ preferences, emotions, and satisfaction. This allows the recommendation procedures to align to the present and expected cognitive states of a user, increasing the combined recommendation and repository use efficiency. The learning algorithm takes into account the results of the cognitive and neural modelling of users’ decision behaviour. Inspirations from nature used in recommendation systems differ from the usual mimicking the biological neural processes. Specifically, a cognitive knowledge recommender may follow a strategy to discover emotional patterns in user behaviour and then adjust the recommendation procedure accordingly. The knowledge of cognitive decision mechanisms helps to optimize recommendation goals. Other cognitive recommendation procedures assist users in creating consistent learning or research groups. The primary application field of the above algorithms is a large knowledge repository coupled with an innovative training platform developed within an ongoing Horizon 2020 research project. © Springer International Publishing AG 2017.


Skulimowski A.M.J.,AGH University of Science and Technology | Skulimowski A.M.J.,Business Center Poland
Proceedings - 2016 16th IEEE International Conference on Computer and Information Technology, CIT 2016, 2016 6th International Symposium on Cloud and Service Computing, IEEE SC2 2016 and 2016 International Symposium on Security and Privacy in Social Networks and Big Data, SocialSec 2016 | Year: 2017

The impact of future Information and Communication Technologies on different spheres of human private, professional and social life attracts a growing attention of a broad public. In particular, the question whether the deployment of intelligent systems will be a chance or a threat to mankind has been considered by many researchers recently. This paper is devoted to an estimation of advanced ICT tools impact on the modes and progress of scientific research in various areas. We will present and discuss the development prospects of selected intelligent technologies such as Global Expert Systems (GES), bi-directional Brain-Computer Interfaces (BCI), or Creativity Support Systems (CSS). The forecasts of their development until 2025 has been presented in a series of papers resulting from a recent ICT foresight project. The above mentioned technologies are supposed to allow scientists to compete with the growing capabilities of intelligent systems to make autonomous decisions in dynamically changing environment. Such systems are referred to as Artificial Autonomous Decision Systems (AADS). We claim that a future scientist endowed with joint capacities of human brain and new technologies will be able to cope with big scientific data growth which exhausts the capacities of any individual researcher. We will present and discuss scenarios that may dominate the development of future scientific methodology. The first one will rely on automation of research, i.e. letting automated expert systems select and process knowledge up to the stage of an edited scientific paper, with relatively minor and ever-decreasing human intervention. The other assumes an intensive development of BCI as an enabling technology for future advanced hybrid intelligent systems. All mitigating approaches are expected to merge, but other optimistic or pessimistic scenarios are also possible. These will be discussed in the Conclusions section of this paper together with recommendations to researchers and R&D policy makers. © 2016 IEEE.


Skulimowski A.M.J.,AGH University of Science and Technology | Skulimowski A.M.J.,Business Center Poland
Communications in Computer and Information Science | Year: 2011

The aim of this paper is to investigate, formulate, and analyse the general rules and principles that govern the evolution of key factors that influence the development of decision support systems (DSS) and models. In order to ela borate a model suitable for medium-term forecasts and recommendations, we have defined eight major elements of Information Society that characterise the evolution of the corresponding digital economy. The evolution of the overall system is described by a discrete-continuous-event system, where the mutual impacts of each of the elements are represented within state-space models. Technological trends and external economic decisions form inputs, while feedback loops allow us to model the influence of technological demand on IT, R&D, production, and supply of DSS. The technological characteristics of the product line evolution modelled in this way can provide clues to software providers about future demand. They can also give R&D and educational institutions some idea on the most likely directions of develop¬ment and demand for IT professionals. As an example, we will model the evolution of decision-support systems and recommenders for 3D-internet-based e-commerce, and their impact on technological progress, consumption patterns and social behaviour. The re sults presented here have been obtained during an IS/IT foresight project carried out in Poland since 2010 and financed by the ERDF. © 2011 Springer-Verlag.


Skulimowski A.M.J.,AGH University of Science and Technology | Skulimowski A.M.J.,Business Center Poland
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2012

This paper presents the theoretical foundations of an intelligent on-line modelling tool capable of processing heterogeneous information on complex techno-economical systems. Its main functionality is to investigate, elicit, and apply rules and principles that govern the development processes of technologies and related markets. Specifically, we will focus on applications of the tool to model the evolution of information technology (IT). We will distinguish several relevant subsystems of the system under study, which describe the demographic, education, global economic trends, as well as specific market factors that determine the demand for and use of IT. The group modelling techniques are implemented in the new tool to enable the collaborative and distributed model building with intelligent verification of entries called 'model wiki'. Based on the information elicited from experts, gathered from the web and professional databases, a discrete-time control model of technological evolution emerges, coupled with a controlled discrete-event system. The latter processes qualitative information and models the influence of external events and trends on the discrete-time control system parameters. We propose novel uncertainty handling techniques capable of processing and combining different types of uncertain information, coming i.a. from Delphi research and forecasts. The quantitative information is dynamically updated by autonomous webcrawlers, following an adaptive intelligent strategy. The resulting model can be used to simulate long-term future trends and scenarios. Its ultimate goal is to perform an optimization process and derive recommendations for decision makers, for example when selecting IT investment strategies in an innovative enterprise. © 2012 Springer-Verlag.


Skulimowski A.M.J.,AGH University of Science and Technology | Skulimowski A.M.J.,Business Center Poland
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2011

This paper presents new approaches to formulating and solving complex real-life decision-making problems, making use of the creativity concept. We assume that the decision-making process is embedded in the system of views and mutual relations between the decision-makers and their surrounding environment, so that creativity, as defined formally in Sec. 2, could play a primary role in the decision-making process. We will investigate multicriteria decision problems, where the decision-maker is unable to fully follow decision-making rules resulting from a standard mathematical formulation of multicriteria optimization problem. This is either due to external conditions (such as the need to make a quick decision, loss of data, or lack of data processing capabilities) or when the decision-maker can manifest creativity related to the hid den internal states of the decision-making pro cess. We will provide a formal definition of freedom of choice (FOC), specifying three levels of FOC for multicriteria decision-making (MCDM) problems. Then we will point out that creativity in decision-making can be explained within the framework of autonomous and free decisions, and that decision-making freedom is a necessary prerequisite for creativity. The methods presented here can be applied to analyzing human decision-making processes and conditions allowing the expression of creativity as well as to designing pathways leading to creative decision-making in artificial autonomous decision systems (AADS). The applications of the latter inc lu de visual information retrieval, financial decision-making with feature identification, intelligent recommenders, to name just a few. © 2011 Springer-Verlag.


Stukan M.,Center of Oncology of Poland | Dudziak M.,Center of Oncology of Poland | Ratajczak K.,Business Center Poland | Grabowski J.P.,Kliniken Essen Mitte
Journal of Ultrasound in Medicine | Year: 2015

The objective of this study was to review the accuracy of indices combining several diagnostic variables, in comparison to other models, sonography alone, and biomarker assays, for predicting benign or malignant ovarian lesions. Different single modalities were reviewed. The most useful complex models were International Ovarian Tumor Analysis (IOTA) sonographic logistic regression model 2 (area under the curve, 0.949), risk of malignancy index-cancer antigen 125-human epididymis protein 4 (0.950), risk of malignancy algorithm (0.953), pelvic mass score (0.960), non-IOTA logistic regression model (0.970), and histoscanning score logistic regression model (0.970). None of the indices was superior to an expert subjective sonographic assessment (0.968). For women with adnexal tumors, indices with high accuracy are available that are applicable in clinical practice and comparable to an expert subjective sonographic assessment for discriminating benign from malignant masses. ©2015 by the American Institute of Ultrasound in Medicine


Skulimowski A.M.J.,AGH University of Science and Technology | Skulimowski A.M.J.,Business Center Poland
International Journal of Systems Science | Year: 2014

In this article, we will investigate the properties of a compromise solution selection method based on modelling the consequences of a decision as factors influencing the decision making in subsequent problems. Specifically, we assume that the constraints and preference structures in the (k + 1)st multicriteria optimisation problem depend on the values of criteria in the k-th problem. To make a decision in the initial problem, the decision maker should take into account the anticipated outcomes of each linked future decision problem. This model can be extended to a network of linked decision problems, such that causal relations are defined between the time-ordered nodes. Multiple edges starting from a decision node correspond to different future scenarios of consequences at this node. In addition, we will define the relation of anticipatory feedback, assuming that some decision makers take into account the anticipated future consequences of their decisions described by a network of optimisers-a class of information processing units introduced in this article. Both relations (causal and anticipatory) form a feedback information model, which makes possible a selection of compromise solutions taking into account the anticipated consequences. We provide constructive algorithms to solve discrete multicriteria decision problems that admit the above preference information structure. An illustrative example is presented in Section 4. Various applications of the above model, including the construction of technology foresight scenarios, are discussed in the final section of this article. © 2014 Taylor and Francis.


Skulimowski A.M.J.,AGH University of Science and Technology | Skulimowski A.M.J.,Business Center Poland
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2013

This paper presents a hypothesis together with evidence related to the use of global knowledge as a holistic expert system. By global expert system (GES) we mean all knowledge sources, bases, repositories, and processing units, regardless of whether they are human, artificial, animal, or hybrid, such that the relation "able to transfer knowledge on immediate demand" forms a connected graph over the elements of the system. A key requirement is that problem solving using GES is an anytime process with respect to the number of information sources taken into account. We conjecture that due to the high and ever-growing level of interconnection of knowledge units, a universal intelligence emerges, which under specific conditions can outperform the intelligence and creativity of any of its individual elements, including humans. It will be shown that this is possible only if an appropriate level of credibility can be assigned to each element of the system, which ensures that users trust the responses. We will design a hybrid supervised-reinforced learning scheme that makes it possible to achieve a satisfactory level of trust in GES query responses. Query processing will apply knowledge fusion methods such as combinations of recommendations and forecasts. © 2013 Springer-Verlag.


Bukowski L.A.,Business Center Poland
International Conference on Industrial Logistics, ICIL 2014 - Conference Proceedings | Year: 2014

Supply chain risk can be seen as any event that might affect continuity of materials and information flow. The risks within the supply chain occur when unexpected events disrupt the flow of materials on their way from initial suppliers to the final customers. In the broad perspective risk exists as a concept embracing two major components: consequences of an activity and associated with it uncertainties. The objective of this paper is to come up with a new framework of disruption risk management for the global supply networks. The core idea of the overall concept is based on the transdisciplinary approach. Copyright © FSB, Zagreb, Croatia, 2014.


Loading Business Center Poland collaborators
Loading Business Center Poland collaborators