כתבה
arXiv cs.AI ·
ETHER: התאמה של תקשורת נובעת לחזרה על פי ניסיון
ETHER: Aligning Emergent Communication for Hindsight Experience Replay
ETHER משפרת כושר ניסיון בלמידה רפלקסיבית מותנית במטרה על ידי למידה רגילה של תפקידי הציווי והפרדיקט.
תקציר מקורי באנגליתarXiv:2307.15494v3 Announce Type: replace-cross Abstract: Hindsight Experience Replay (HER) enhances sample efficiency in goal-conditioned reinforcement learning (RL) by relabelling failed trajectories with goals that were actually achieved. However, HER assumes access to a goal relabelling function and a predicate function that determines whether a goal has been satisfied. These assumptions break down in instruction-following tasks, where goals are expressed in natural language and differ from the state space. We formalize this as the Hindsight Reinforcement Learning problem, which shows the need to jointly learn these functions alongside the RL policy. To address it, we propose ETHER (Emergent Textual Hindsight Experience Replay), an agent that leverages Emergent Communication. ETHER use
קרא במקור המקורי
arxiv.org
פתח כתבה מקורית