Yan, F.; Iliyasu, A.M.; Hirota, K. Conceptual Framework for Quantum Affective Computing and Its Use in Fusion of Multi-Robot Emotions. Electronics2021, 10, 100.
Yan, F.; Iliyasu, A.M.; Hirota, K. Conceptual Framework for Quantum Affective Computing and Its Use in Fusion of Multi-Robot Emotions. Electronics 2021, 10, 100.
Yan, F.; Iliyasu, A.M.; Hirota, K. Conceptual Framework for Quantum Affective Computing and Its Use in Fusion of Multi-Robot Emotions. Electronics2021, 10, 100.
Yan, F.; Iliyasu, A.M.; Hirota, K. Conceptual Framework for Quantum Affective Computing and Its Use in Fusion of Multi-Robot Emotions. Electronics 2021, 10, 100.
Abstract
This study presents a modest attempt to interpret, formulate, and manipulate emotion of robots within the precepts of quantum mechanics. Our proposed framework encodes the emotion information as a superposition state whilst unitary operators are used to manipulate the transition of the emotion states which are recovered via appropriate quantum measurement operations. The framework described provides essential steps towards exploiting the potency of quantum mechanics in a quantum affective computing paradigm. Further, the emotions of multi-robots in a specified communication scenario are fused using quantum entanglement thereby reducing the number of qubits required to capture the emotion states of all the robots in the environment, and fewer quantum gates are needed to transform the emotion of all or part of the robots from one state to another. In addition to the mathematical rigours expected of the proposed framework, we present a few simulation-based demonstrations to illustrate its feasibility and effectiveness. This exposition is an important step in the transition of formulations of emotional intelligence to the quantum era.
Keywords
Affective computing; Artificial intelligence; Quantum emotion; Emotion fusion; Social robots
Subject
Engineering, Electrical and Electronic Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
