Jadwiga Sobieska-Karpińska

Application of the consensus method in a multiagent financial decision support system

Abstract Financial decisions are supported by different methods, based mainly on statistics, mathematics, behaviorism, artificial intelligence or experts’ opinion sentiment analysis. The main problem is that under conditions of risk and uncertainty predicting financial markets can be very difficult. This paper presents an approach to investment strategy design for a multiagent system which supports investment decisions on the stock market. Individual components and functionalities of the multiagent financial decision support system method have been briefly described. On the basis of decisions generated by agents, the Supervisor Agent uses a consensus method to generate a satisfactory rate of return and reduce the level of risk associated with investing in a financial instrument. Verification of the effectiveness of the strategy has been conducted using investments on the Warsaw Stock Exchange.

A New Distance Function for Consensus Determination in Decision Support Systems

Consensus methods are used mainly to solve conflicts of knowledge in decision support systems. Generally speaking, conflicts of knowledge arise from the fact that system nodes (for example, agents, experts) may present various decisions or solutions to the user. This may be due to the use of various methods of decision support or different information sources by agents/experts. If there is a conflict of knowledge in the system and they are not automatically resolving the system cannot generate the final decision, and hence - the decision maker will not receive hints from the system. The use of consensus methods eliminates this problem, because they enable to solve conflicts of knowledge in near real time. At the same time they guarantee the achievement of a good compromise. However, the effective determination of consensus depends, among other, on the correct definition of the distance function.

Identification of the knowledge conflicts' sources in the architecture of cognitive agents supporting decision-making process

This article 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 causes of knowledge conflicts was indicated. The final part of article contains the analysis of sources of knowledge conflicts and their examples related to decision-making process.