Abstract

This paper presents a hybrid approach to decision-making, capable of calibrating a trade-off between accuracy and response time by using multiple decision-making techniques to reach a solution of a decision problem. Each device employed by the decision-making system should also be able to learn from solutions suggested by other devices. This can be achieved by applying adaptive techniques, which make possible to change each device's behavior according to the input received. This process happens autonomously, without human interference.

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