# Towards Cognitive AI Systems: a Survey and Prospective on Neuro-Symbolic AI

arXiv: https://arxiv.org/abs/2401.01040 · HTML: https://mlsanity.com/paper/2401.01040/

## Key facts

- Cited by 24 papers in the map (data through 14 Oct 2026).
- Builds on 24 of its 36 references that are in the map.
- First posted on arXiv 2 Jan 2024.

## Builds on (most cited first, 24 of 24)

- [Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm](https://mlsanity.com/paper/1712.01815/) (2017)
- [The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision](https://mlsanity.com/paper/1904.12584/) (2019)
- [Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding](https://mlsanity.com/paper/1810.02338/) (2018)
- [Deep Learning for Symbolic Mathematics](https://mlsanity.com/paper/1912.01412/) (2019)
- [Sustainable AI: Environmental Implications, Challenges and Opportunities](https://mlsanity.com/paper/2111.00364/) (2021)
- [RAVEN: A Dataset for Relational and Analogical Visual rEasoNing](https://mlsanity.com/paper/1903.02741/) (2019)
- [Learning Explanatory Rules from Noisy Data](https://mlsanity.com/paper/1711.04574/) (2017)
- [Logic Tensor Networks](https://mlsanity.com/paper/2012.13635/) (2020)
- [Neural-Symbolic Learning and Reasoning: A Survey and Interpretation](https://mlsanity.com/paper/1711.03902/) (2017)
- [Neural-Symbolic Computing: An Effective Methodology for Principled Integration of Machine Learning and Reasoning](https://mlsanity.com/paper/1905.06088/) (2019)
- [Neural Logic Machines](https://mlsanity.com/paper/1904.11694/) (2019)
- [Logical Neural Networks](https://mlsanity.com/paper/2006.13155/) (2020)
- [Graph Neural Networks Meet Neural-Symbolic Computing: A Survey and Perspective](https://mlsanity.com/paper/2003.00330/) (2020)
- [Stratified Rule-Aware Network for Abstract Visual Reasoning](https://mlsanity.com/paper/2002.06838/) (2020)
- [Thinking Fast and Slow in AI](https://mlsanity.com/paper/2010.06002/) (2020)
- [A Neuro-vector-symbolic Architecture for Solving Raven's Progressive Matrices](https://mlsanity.com/paper/2203.04571/) (2022)
- [Ontology Reasoning with Deep Neural Networks](https://mlsanity.com/paper/1808.07980/) (2018)
- [Towards Data-and Knowledge-Driven Artificial Intelligence: A Survey on Neuro-Symbolic Computing](https://mlsanity.com/paper/2210.15889/) (2022)
- [NeuPSL: Neural Probabilistic Soft Logic](https://mlsanity.com/paper/2205.14268/) (2022)
- [Neuro-Symbolic AI: An Emerging Class of AI Workloads and their Characterization](https://mlsanity.com/paper/2109.06133/) (2021)
- [PyReason: Software for Open World Temporal Logic](https://mlsanity.com/paper/2302.13482/) (2023)
- [Analyzing and Improving Fault Tolerance of Learning-Based Navigation Systems](https://mlsanity.com/paper/2111.04957/) (2021)
- [Roofline Model for UAVs: A Bottleneck Analysis Tool for Onboard Compute Characterization of Autonomous Unmanned Aerial Vehicles](https://mlsanity.com/paper/2204.10898/) (2022)
- [Robotic Computing on FPGAs: Current Progress, Research Challenges, and Opportunities](https://mlsanity.com/paper/2205.07149/) (2022)

## Built on by (most cited first, 24 of 24)

- [Towards Efficient Neuro-Symbolic AI: From Workload Characterization to Hardware Architecture](https://mlsanity.com/paper/2409.13153/) (2024)
- [Dspy-based Neural-Symbolic Pipeline to Enhance Spatial Reasoning in LLMs](https://mlsanity.com/paper/2411.18564/) (2024)
- [ProSLM : A Prolog Synergized Language Model for explainable Domain Specific Knowledge Based Question Answering](https://mlsanity.com/paper/2409.11589/) (2024)
- [A Study on Neuro-Symbolic Artificial Intelligence: Healthcare Perspectives](https://mlsanity.com/paper/2503.18213/) (2025)
- [Egocentric Co-Pilot: Web-Native Smart-Glasses Agents for Assistive Egocentric AI](https://mlsanity.com/paper/2603.01104/) (2026)
- [H3DFact: Heterogeneous 3D Integrated CIM for Factorization with Holographic Perceptual Representations](https://mlsanity.com/paper/2404.04173/) (2024)
- [Towards certifiable AI in aviation: landscape, challenges, and opportunities](https://mlsanity.com/paper/2409.08666/) (2024)
- [Foundations of a Developmental Design Paradigm for Integrated Continual Learning, Deliberative Behavior, and Comprehensibility](https://mlsanity.com/paper/2502.13935/) (2025)
- [Symbolic Intermediaries as a Linguistic-Numerical Interface for LLM-Driven Geometric Reasoning](https://mlsanity.com/paper/2505.17607/) (2025)
- [Building Trustworthy AI: Transparent AI Systems via Large Language Models, Ontologies, and Logical Reasoning (TranspNet)](https://mlsanity.com/paper/2411.08469/) (2024)
- [NSFlow: An End-to-End FPGA Framework with Scalable Dataflow Architecture for Neuro-Symbolic AI](https://mlsanity.com/paper/2504.19323/) (2025)
- [On the Parallels Between Evolutionary Theory and the State of AI](https://mlsanity.com/paper/2505.23774/) (2025)
- [From Craft to Constitution: A Governance-First Paradigm for Principled Agent Engineering](https://mlsanity.com/paper/2510.13857/) (2025)
- [A neurosymbolic Approach with Epistemic Deep Learning for Hierarchical Image Classification](https://mlsanity.com/paper/2605.16383/) (2026)
- [MixGCN: Scalable GCN Training by Mixture of Parallelism and Mixture of Accelerators](https://mlsanity.com/paper/2501.01951/) (2025)
- [Evolutionary Developmental Biology Can Serve as the Conceptual Foundation for a New Design Paradigm in Artificial Intelligence](https://mlsanity.com/paper/2506.12891/) (2025)
- [Bridging the Gap Between Scientific Laws Derived by AI Systems and Canonical Knowledge via Abductive Inference with AI-Noether](https://mlsanity.com/paper/2509.23004/) (2025)
- [Multi-task GINN-LP for Multi-target Symbolic Regression](https://mlsanity.com/paper/2511.13463/) (2025)
- [A Neuro-Symbolic Framework for Accountability in Public-Sector AI](https://mlsanity.com/paper/2512.12109/) (2025)
- [REASON: Accelerating Probabilistic Logical Reasoning for Scalable Neuro-Symbolic Intelligence](https://mlsanity.com/paper/2601.20784/) (2026)
- [SciTaRC: A Plan-Annotated Scientific Tabular QA Benchmark for Language Reasoning and Complex Computation](https://mlsanity.com/paper/2603.08910/) (2026)
- [ANNEAL: Adapting LLM Agents via Governed Symbolic Patch Learning](https://mlsanity.com/paper/2605.16309/) (2026)
- [Neuro-Symbolic Agents for Regulated Process Automation: Challenges and Research Agenda](https://mlsanity.com/paper/2606.13405/) (2026)
- [A Task-Centric Ontology and Deterministic Domain Rules as a Verifiable Core for AI-Assisted Chemistry Problem Solving](https://mlsanity.com/paper/2608.26164/) (2026)

## Abstract (arXiv)

The remarkable advancements in artificial intelligence (AI), primarily driven by deep neural networks, have significantly impacted various aspects of our lives. However, the current challenges surrounding unsustainable computational trajectories, limited robustness, and a lack of explainability call for the development of next-generation AI systems. Neuro-symbolic AI (NSAI) emerges as a promising paradigm, fusing neural, symbolic, and probabilistic approaches to enhance interpretability, robustness, and trustworthiness while facilitating learning from much less data. Recent NSAI systems have demonstrated great potential in collaborative human-AI scenarios with reasoning and cognitive capabilities. In this paper, we provide a systematic review of recent progress in NSAI and analyze the performance characteristics and computational operators of NSAI models. Furthermore, we discuss the challenges and potential future directions of NSAI from both system and architectural perspectives.