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EN
The article presents a proposition of a universal model of knowledge conflict resolving using consensus methods, which can be used in a multi-agent decision support system. Knowledge conflicts often appear, when individual agents generate different solutions of the same problem. It is very difficult for the user – decision-maker to make a good decision because the analysis of solutions generated by agents is very time-consuming and the decision must be made quickly. Moreover, selecting one of the decisions on the basis of the experience of the decision-maker is very risky, because he/she could choose the worst solution. Consensus methods, however, allow to agree, on the basis of the solutions generated by agents, one solution, which is a compromise. As a consequence, reducing the time and decreasing the risk level of the decision taking process, to enable the functioning of the enterprise in more flexible.
EN
The authors of this paper present an approach to trading strategy design for an A-Trader multi-agent system which supports investment decisions on the stock market. The functionalities of the system, and the main component, the Supervisor Agent, used as a strategy a consensus method to reduce the level of investment risk, are described. The consensus method allows the coordination of the work of agents, and on the basis of the decisions provided by the agents presents trading advice to the investor. The strategy has been tested on FOREX quotes, namely on the pair USD/PLN. The results of the research are described and the directions of the further development of the platform are provided in the conclusion.
EN
An iterative multicriteria closed-auction conducted with the use of a multi-agent computer-based system is analyzed. This system supports the submission of offers, multicriteria analysis carried out by the organizer of the auction, simulation, and analysis of the behavior of competing bidders. Analysis of incentive compatible decisions is the main subject of this research. A mathematical formulation of the decision making problem and selected results of a bidding session conducted using this system are presented and analyzed.
EN
Background: Smart buildings are one of the major application areas of technologies bound to embedded systems and the Internet of things. Such systems have to be adaptable and flexible in order to provide better services to its residents. Modelling such systems is an open research question. Herein, the question is approached using an organizational modelling methodology bound to the principles of the learning organization. Objectives: Providing a higher level of abstraction for understanding, developing and maintaining smart residential buildings in a more human understandable form. Methods/Approach: Organization theory provides us with the necessary concepts and methodology to approach complex organizational systems. Results: A set of principles for building learning agent organizations, a formalization of learning processes for agents, a framework for modelling knowledge transfer between agents and the environment, and a tailored organizational structure for smart residential buildings based on Nonaka’s hypertext organizational form. Conclusions: Organization theory is a promising field of research when dealing with complex engineering systems
EN
The main purpose of the paper is to provide the framework for organizational creativity computer support. Our considerations [Bratnicki, Kisielnicki, Olszak 2014] on the issue of organizational creativity have resulted to the integration of two research areas: organizational creativity (from the strategic perspective and dynamic capabilities) and ICT. Consequently, we have proposed the holistic concept of organizational creativity computer support. To create it, Hevner et al. [2004] design-science research guidelines were used.
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