EvolvingBrain: adaptive skill system for multi-modal agents (arXiv:2610.20786v1)
New arXiv paper proposes EvolvingBrain, an adaptive skill system that enables agent self-evolution in open-world settings via two components: Stratified Skill Self‑Evolution (extracting and organizing procedural and problematic patterns into a multi-granularity Stratified Skill Architecture) and State‑Aware Adaptive Execution (using Structured Abstractive Memory to fuse skills according to agent state). Experiments on VAB‑Minecraft and DiscoveryWorld reportedly improve success rates and generalization; authors say code will be released with the camera‑ready version.