Multimodal Deep Q-Network for Environmental Adaptation of Robotized Plants

Though keeping pets increases communication among family and colleagues, it has challenges, such as allergies and the need for environmental management. As an alternative, we propose the robotized plant, designed to enhance group communication through nurturing activities. We posit that environmental adaptation is essential for the robotized plant to coexist with its caretakers over extended periods. To achieve this, we aim to optimize its vocalization behavior by considering both internal and external states using a Multimodal Deep Q-Network (DQN). This paper evaluates the feasibility of environmental adaptation by analyzing the learning outcomes of the proposed system under various simulated conditions.