A Recursive Neural Network (RecNN) is a type of neural network architecture that is designed to handle hierarchical or tree-structured data. Unlike traditional feedforward neural networks, which process data in a linear sequence, RecNNs can operate on structures like trees or graphs where information flows along multiple paths. Recursive Neural Networks (RecNNs) are a part of artificial intelligence development (AI). They are a type of neural network architecture that falls under the broader category of machine learning, which is a subset of AI.

In a RecNN, the network is recursively applied to substructures of the input data. This means that the same set of weights and biases are used at different levels of the tree, allowing the network to process information hierarchically.