Neuro-Symbolic AI for Cognitive Robotics: Bridging Perception and Reasoning

Abstract

The development of Neuro-Symbolic Artificial Intelligence (NSAI) marks a landmark in the development of cognitive robotics and it provides an integrative platform that is based on the ability to adaptively learn new tasks through neural networks and on the ability of the symbolic logic to engage in the structured reasoning processes. The traditional AI paradigms have had difficulties in integrating perception and reasoning, which are critical parts of human thought, such that they produce systems that may be good at recognizing patterns in sensory stimuli but can not be explained or they may produce logical reasoning in more unstructured settings with no flexibility. Neuro-Symbolic AI fills this gap by allowing robots to sense complex sensory information and generate symbolic representations and reason about these abstractions in a human-like way. Such a combination of subsymbolic and symbolic intelligence enables cognitive robots to learn to read pictures, to understand cause and effect, and think about things and act according to contextual knowledge. This paper will discuss the theoretical basis and practical applications of NSAI architectures to robotic cognition, with focus to how hybrid reasoning systems increase generalization, interpretability and safety of autonomous systems. It further reviews current studies which combine deep neural models with symbolic inference engines, which enable two way information flow between perception units with reasoning strata. Through the study and examination of the existing patterns in cognitive robotics, the present paper demonstrates the radical nature of NSAI in overcoming the deep-seated gap between data-driven learning and rule-based logic. The synthesis of these paradigms is not only a step towards robot autonomy and adaptability but also resolves the ethical concerns, transparency, and trust concerns of the AI-based decision-making process. Finally, Neuro-Symbolic AI is a positive advance to the creation of actually intelligent robots that can cognize, describe, and act in the physical and social worlds as coherent and accountable humans do.