10 papers
Discovering Diverse Planning Policies for Multimodal Embodied Agents with Quality-Diversity Optimization
Pengfei Xu, Yong Liu, Xiaoya Nan +2
Multimodal embodied agents are increasingly required to solve long-horizon tasks by integrating visual observations, textual goals, and interaction history into closed-loop decisio…
Structure-Conditioned Actor-Critic Branches for Quality-Diversity Reinforcement Learning
Lianrong Zuo, Peilan Xu, Yong Liu +1
Quality-diversity reinforcement learning (QD-RL) aims to construct policy repertoires that contain both high-performing and behaviorally diverse policies. Existing QD-RL methods ma…
Co-evolving Agent Architectures and Interpretable Reasoning for Automated Optimization
Jiahao Huang, Peilan Xu, Xiaoya Nan +1
Automating operations research (OR) with large language models (LLMs) remains limited by hand-crafted reasoning--execution workflows. Complex OR tasks require adaptive coordination…
Multi-Party Multi-Objective Optimization as Consensus Search: Runtime Analysis of Cross-Party Recombination
Xiaolei Fang, Peilan Xu, Wenjian Luo
Multi-party multi-objective optimization problems (MPMOPs) require consensus among autonomous decision makers and therefore differ from flattened many-objective formulations. Exist…
Think Before Writing: Feature-Level Multi-Objective Optimization for Generative Citation Visibility
Zikang Liu, Peilan Xu
Generative answer engines expose content through selective citation rather than ranked retrieval, fundamentally altering how visibility is determined. This shift calls for new opti…
A Novel Immune Algorithm for Multiparty Multiobjective Optimization
Kesheng Chen, Wenjian Luo, Qi Zhou +3
Traditional multiobjective optimization problems (MOPs) are insufficiently equipped for scenarios involving multiple decision makers (DMs), which are prevalent in many practical ap…