Quantum-Inspired Bidirectional Associative Memory for Human-Robot Communication

The emerging research area of a quantum-inspired computing has been applied to various ̄eld such as computational intelligence, and showed its superior abilities. However, most existing researches are focused on theoretical simulations, and have not been implemented in systems under practical environment. For human–robot communication, associative memory becomes essential for multi-modal communication. However, it always su®ers from low memory capacity and recall reliability. In this paper, we propose a quantum-inspired bidirectional associative memory with fuzzy inference. We show that fuzzy inference satis ̄es basic postulates of quantum mechanics, but also learning algorithm for weight matrix in associative memory. In addition, we construct a communication system with robot partner using proposed model. This is the ̄rst successful attempt to overcome conventional problems in associative memory model with a robot application.