Abstract-Providing financial e-services in the all areas involves taking decisions processes. Existing systems, also multi-agent systems, usually include only one of the earlier mentioned areas, and they are closed systems, available only to a small group of users. In addition, agents' knowledge in these systems is characterized by a certain degree of heterogeneity. Since in the decisive process one final decision is required, knowledge shall be automatically integrated. The aim of this paper is presentation of the author's method for knowledge integration in multi-agent decision support system of financial e-services. The first part of paper presents an architecture of the developed system, functioning of selected agents and a structure of agents' knowledge representation. Next, the developed method for integration of knowledge has been described. The last part of paper presents the results of research experiment to evaluate the effectiveness of the system and the developed method.
The aim of the chapter is to develop an approach for improving quality management in flexographic printing on packages using cognitive agent. A hybrid agents' architecture based on the learning intelligent distribution agent architecture (LIDA) and hierarchical temporal memory has been developed. Such approach has not been developed before; therefore, it is the main contribution of this chapter. The first part of the chapter presents the introduction to the research problem and background. Next, research methodology and the LIDA cognitive agents have been described. The main part of chapter presents the cognitive agent's architecture and functionality related to quality management in flexographic printing. The last part presents discussion, future works, and major conclusions.
This paper presents the problem of knowledge conflicts identification in the architecture of cognitive agents. The agents operate at the decision support systems. The types and the sample of cognitive agents architecture was characterized in the first part of article. Next, the customer relationship management agent was described and the causes of knowledge conflicts were indicated. The final part of article contains the analysis of sources of knowledge conflicts and their examples related to decision-making process.
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