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Abstract

The problem of rational investment and allocation of funds for an agent with individual goals and experiences is presented in this paper. Simon Herbert’s model of decision making, the EPAM model of intuition as a decision tree with the accompanying Soar software which is a modern cognitive architecture for modeling intelligent agents are considered. The state space and selection of decision rules for determining the optimal solution are presented, emphasizing the role of intuition. A decision-making scheme is presented, leading to the acquisition of distinct experiences resulting in an increase in the procedural knowledge stored in the long-term memory. The next stage is to visualize the decision-making process in the working memory in order to satisfactorily allocate funds into three categories. The results obtained indicate the intuitively correct decision according to an assumed quality factor which is the level of overall agent satisfaction. Reference is also made to the possible application of GAN neural networks, showing their potential in supporting intuitive decision making in the stock market. The considerations confirm the validity of an intuitive approach to business solutions and also enable a closer look at multidimensional aspects of intuition. The considerations confirm the validity of the intuitive approach to business solutions, as well as presenting an insight into multidimensional aspects of intuition itself.