Formalisms inspired by Quantum theory have been used in Cognitive Science for decades. Indeed, Quantum-Like (QL) approaches provide descriptive features that are inherently suitable for perception, cognition, and decision processing. A preliminary study on the feasibility of a QL robot perception model has been carried out for a robot with limited sensing capabilities. In this paper, we generalize such a model for multi-sensory inputs, creating a multidimensional world representation directly based on sensor readings. Given a 3-dimensional case study, we highlight how this model provides a compact and elegant representation, embodying features that are extremely useful for modeling uncertainty and decision. Moreover, the model enables to naturally define query operators to inspect any world state, which answers quantifies the robot's degree of belief on that state.

中文翻译：

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类量子机器人感知模型中的多感官集成

受量子理论启发的形式主义已经在认知科学中使用了几十年。事实上，类量子 (QL) 方法提供了本质上适用于感知、认知和决策处理的描述性特征。针对感知能力有限的机器人，对 QL 机器人感知模型的可行性进行了初步研究。在本文中，我们将这种模型推广到多感官输入，直接基于传感器读数创建多维世界表示。给出一个 3 维案例研究，我们强调该模型如何提供紧凑而优雅的表示，体现了对不确定性和决策建模非常有用的特征。此外，该模型能够自然地定义查询运算符来检查任何世界状态，这些状态的答案量化了机器人的“