concept

neural perception module

Also known as: neural module, neural knowledge modules, neural perception module, neural modules

Facts (11)

Sources

A Comprehensive Review of Neuro-symbolic AI for Robustness ... link.springer.com Springer Dec 9, 2025 9 facts

claimModular neuro-symbolic architectures support heterogeneous specialization, allowing each subcomponent to leverage domain-specific advances, though they face challenges in propagating corrective signals back to the neural module when inconsistencies emerge.

referenceRobotics and autonomous systems often utilize a two-tier neuro-symbolic architecture where the first tier uses neural perception modules, such as convolutional neural networks, vision transformers, or event-based sensors, to segment scenes and instantiate logical atoms, while the second tier uses a symbolic task and motion planner to synthesize policies and enforce safety invariants.

procedureThe neuro-symbolic pipeline for handling uncertainty consists of three stages: (1) the Neural Module processes raw inputs to generate probabilistic outputs like soft class labels or confidence scores; (2) the Probabilistic Logic layer receives these outputs, where logical rules are assigned probabilistic weights and soft constraints to account for noise or ambiguity; (3) the Symbolic Reasoner performs rule-based inference using these uncertain predicates, and the final decision is validated against confidence thresholds.

referenceThe 'Neuro: Symbolic -> Neuro' architecture follows a pipeline configuration where a neural module processes raw inputs into symbolic representations, which are then consumed by a symbolic reasoner, with feedback from the symbolic module used to iteratively refine the neural model.

referenceModular architectures in neuro-symbolic AI retain clear separability between neural and symbolic subsystems, where neural modules output probabilistic facts or distributions that are consumed by symbolic solvers for logical inference or planning.

procedureNeuro-symbolic robustness pipelines operate by having a neural perception module convert raw sensory inputs into probabilistic concept embeddings, which are then injected into a symbolic knowledge store and a logical reasoner or planner. The reasoner combines symbolic priors with neural evidence to propose candidate decisions, which are scrutinized by a verifier enforcing formal constraints. Verified outputs are released as actions, while violations trigger a feedback loop that supplies explanatory traces for explanation-based fine-tuning.

claimThe learning-reasoning paradigm embodies a bidirectional interplay where neural and symbolic modules iteratively inform and refine each other, with neural components extracting structured hypotheses and symbolic modules performing inference and feeding back structured signals.

referenceA common neuro-symbolic architecture involves neural modules outputting soft probabilistic estimates, which are then processed by a symbolic reasoning layer that uses confidence thresholds and probabilistic logic rules to refine final decisions.

imageFigure 10 in the source text illustrates a neuro-symbolic decision stack where raw sensory input is processed by a Neural Perception module into interpretable Concepts, which then feed into a Rules layer to enforce domain-specific logic before a decision is made. The diagram also shows human control channels that allow a domain expert to override or relabel individual concepts, redirect rule evaluation, and critique the Explanation Interface (such as saliency maps, concept heat maps, or rule traces) to refine rule weights and concept classifiers.

Survey and analysis of hallucinations in large language models frontiersin.org Frontiers Sep 29, 2025 1 fact

referenceYao et al. (2022) proposed the integration of symbolic and neural knowledge modules to mitigate hallucinations.

Complexity and the Evolution of Consciousness | Biological Theory link.springer.com Springer Sep 14, 2022 1 fact

claimThomas Brunet and Detlev Arendt described the early evolution of neural and contractile modules in stem eukaryotes, linking damage response to action potentials.