IJCAI

Neuro-Symbolic Artificial Intelligence: A Task-Directed Survey in the Black-Box Models Era

神经符号人工智能：在黑盒模型时代任务导向的综述

Giovanni Pio Delvecchio, Lorenzo Molfetta, Gianluca Moro

AI总结 本研究综述探讨神经符号方法在任务导向中的进展，旨在提升可解释性和推理能力，并为现实任务提供可解释的NeSy方法资源。

Comments Accepted for publication at IJCAI-25. Please cite the definitive, copyrighted, peer reviewed and edited version of this Article published in IJCAI 25, pp. 4196-4176, 2025. DOI: https://doi.org/10.24963/ijcai.2025/1157

Journal ref Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, 2025, pages 10418-10426

Post Hoc Extraction of Pareto Fronts for Continuous Control

事后提取帕累托前沿用于连续控制

Raghav Thakar, Gaurav Dixit, Kagan Tumer

机构 * The Collaborative Robotics and Intelligent Systems (CoRIS) Institute（协作机器人与智能系统研究所） 纠错

AI总结 MAPEX是一种离线多目标强化学习方法，通过重用预训练策略和回放缓冲区，以低样本成本提取帕累托前沿，平衡多个目标。

Comments 10 pages, 4 figures. Submitted to IJCAI 2026