Title: AGEL-Comp: A Neuro-Symbolic Framework for Compositional Generalization in Interactive Agents

Source: http://arxiv.org/abs/2604.26522v1

Summary:

This framework introduces a principled neuro-symbolic architecture that addresses systemic failures in compositional generalization within LLM-based agents. It integrates dynamic causal program graphs, inductive logic programming, and neural theorem proving to enable agents to build explicit and interpretable world models.