A context-aware fuzzy linguistic consensus model supporting innovation processes

Nowadays, many research works are moving toward the definition of models for human decision support systems within business process executions. Existing solutions, in general, do not take into account the context in which such processes run but they provide rigid models that could erroneously support decision-making activities when a different context needs to be considered. This work focuses on the definition of a framework to support and trace human decision-making activities, in business processes, when more heterogeneous decision-makers have to find a consensus to select one alternative among the others. One class of such processes is that of Innovation Processes. In particular, the main result described here is a Contextaware Fuzzy Linguistic Consensus Model, based on Fuzzy Logic, Semantic Web technologies and Reinforcement Learning, that considers heterogeneous decision makers with different levels of influence (assigned by considering their past decisions) in the context where the decision activity takes place.