International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Neuro-Symbolic AI for Developing Robotic Intuition Toward Human-Like Understanding, Self-Awareness, and Self-Evolving Intelligence |
|---|---|
| ABSTRACT | Modern robotic systems demonstrate strong performance in structured environments but continue to struggle in ambiguous or dynamic contexts that require flexible reasoning, contextual interpretation, and intuitive decision-making. While deep learning enables perception and pattern recognition, it lacks intrinsic reasoning and explainability, whereas symbolic artificial intelligence supports structured reasoning but fails to scale under real-world uncertainty. Neuro-symbolic artificial intelligence (NSAI), which integrates neural learning with symbolic reasoning, offers a promising pathway toward humanlike robotic cognition. This review surveys key developments in NSAI for robotics, emphasizing hybrid architectures that enable intuition, contextual understanding, self-awareness, and adaptive intelligence. By synthesizing advances across cognitive modeling, meta-learning, and explainable reasoning, the paper outlines emerging frameworks for robotic self-reflection and self-evolving intelligence. Ethical, safety, and long-term autonomy considerations are also discussed. NSAI is positioned as a foundational paradigm for the next generation of interpretable, trustworthy, and cognitively capable autonomous robotic systems. |
| AUTHOR | MAHESH SURESH KOLEKAR, DR. MANISHA BHARATI MSc. Student, Department of Data Science and AI, SPPU, Pune, India Guide, Professor at DOT, SPPU, Pune, India |
| VOLUME | 184 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1405064 |
| pdf/64_Neuro-Symbolic AI for Developing Robotic Intuition Toward Human-Like Understanding, Self-Awareness, and Self-Evolving Intelligence.pdf | |
| KEYWORDS | |
| References | [1] A. d’Avila Garcez et al. , Neuro-Symbolic AI: The Third Wave of Artificial Intelligence. Springer, 2021. [2] L. Serafini and A. d’Avila Garcez, “Logic tensor networks,” in Proc. IJCAI, 2017. [3] D. Silver et al., “Reward is enough,” Artificial Intelligence, 2021. [4] R. Sun, Anatomy of Intelligence. MIT Press, 2020. [5] J. Pearl, The Book of Why. Basic Books, 2018. |
