ICLR 2026 Workshop二轮征稿开启：聚焦终身智能体的学习、对齐、演化

Core Insights - Artificial Intelligence is at a new turning point, with AI Agents based on Large Language Models (LLM), Reinforcement Learning (RL), and Embodied AI rapidly emerging, showcasing multi-dimensional capabilities such as planning, reasoning, tool usage, and autonomous decision-making [2] - The current mainstream paradigm faces critical bottlenecks, necessitating a shift towards Lifelong Agents that can continuously learn, align over the long term, evolve autonomously, perceive resources, and be sustainably deployed [2] Workshop Overview - The Lifelong Agent Workshop, initiated by institutions like UIUC, Edinburgh, Oxford, and Princeton during the ICLR 2026 conference, aims to create a cross-disciplinary forum to systematically advance the Lifelong Agent research paradigm [3] - The workshop will address key issues related to Lifelong Agents, including language intelligence, reinforcement learning, embodied systems, multi-agent collaboration, and AI for science, defining the next technological milestone for Agent development [3] Challenges in Lifelong Learning - The phenomenon of catastrophic forgetting remains a significant challenge when models face dynamic and out-of-distribution (OOD) tasks, leading to decreased alignment consistency as user goals, environmental feedback, and contextual constraints evolve over time [4] - Real-world operational constraints such as computational power, token, energy, and interaction costs hinder the sustainability of these systems [4] Workshop Details - The workshop is scheduled for April 26-27, 2026, in Rio de Janeiro, featuring a hybrid format for participation [8] - The expected attendance is between 200-400 in-person participants and 500-600 online attendees [8] Submission Topics - The workshop encourages cross-disciplinary research focused on long-term operational Agents, particularly in areas such as Lifelong Learning, Lifelong Alignment, Self-Evolving Agents, and Embodied & Real-World Lifelong Agents [7] - Specific topics include memory-augmented RL, continual exploration, user goal change modeling, and multi-agent lifelong collaboration ecosystems [9][10] Future Directions - Lifelong Agents represent an upgrade in intelligent paradigms, aiming to create stable, autonomous, and sustainably growing systems that can contribute to scientific discovery and cross-modal interaction [11] - The workshop seeks to push Lifelong Agents towards becoming the next significant advancement in the field, addressing challenges related to resource-constrained learning and reasoning [12]