论文标题
在量子样机器人感知模型中的多敏化集成
Multi-sensory Integration in a Quantum-Like Robot Perception Model
论文作者
论文摘要
数十年来，受量子理论启发的形式主义已在认知科学中被使用。实际上，量子样（QL）方法提供了固有地适合感知，认知和决策处理的描述性特征。已经针对具有有限感应能力的机器人进行了有关QL机器人感知模型可行性的初步研究。在本文中，我们将这种模型概括为多感官输入，直接基于传感器读数创建多维世界表示。考虑到三维案例研究，我们强调了该模型如何提供紧凑而优雅的表示形式，体现了对建模不确定性和决策极为有用的功能。此外，该模型使自然定义查询操作员可以检查任何世界状态，该州的答案量化了机器人对该州的信念程度。
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.
