Fuzzy cognitive maps for artificial emotions forecasting

At the present, emotion is considered as a critical point of human behaviour, and thus it should be embedded within the reasoning module when an intelligent system or a autonomous robot aims to emulate or anticipate human reactions. Therefore, current research in Artificial Intelligence shows an increasing interest in artificial emotion research for developing human-like systems. Based on Thayer's emotion model and Fuzzy Cognitive Maps, this paper presents a proposal for forecasting artificial emotions. It provides an innovative method for forecasting artificial emotions and designing an affective decision system. This work includes an experiment with three simulated artificial scenarios for testing the proposal. Each scenario generate different emotions according to the artificial experimental model.

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► Autonomous systems should decide autonomously without or with scarce human interference how to respond to changes in their contexts and environments.
► Emotion could be embedded within the reasoning module when an intelligent system or a autonomous robot aims to emulate or anticipate human reactions.
► Based on Thayer's emotion model and Fuzzy Cognitive Maps, this paper presents a proposal for artificial emotions forecasting or simulation.