Hierarchical models of the team learning in a dynamic environment

In this paper, we study the problems of learning in fuzzy perceptrons and dynamic team models. The dynamic team models are extended to hierarchical models of team learning. The various concepts of perceptrons and fuzzy sets are introduced to the extended dynamic team models. Then, hierarchical dynamic team models are proposed. In addition, this paper presents the new definition of the expected utility of the dynamic team. This expected utility is defined by a causal fuzzy information structure, a local fuzzy decision rule and a supreme team decision rule. The proposed hierarchical models of dynamic team learning contain fuzzy perceptrons as special cases. These models use learning rules to adjust a weight matrix interpreted as the intensity of the team member´s informal human relations. These relations are expressed by the ideas of fuzzy relations. The relationship between proposed dynamic team models and fuzzy perceptrons is discussed. Fuzzy perceptron algorithms are also given in this research