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cs.AI2025
Boosting Universal LLM Reward Design through Heuristic Reward Observation Space Evolution
Zen Kit Heng, Zimeng Zhao, Tianhao Wu +4
Large Language Models (LLMs) are emerging as promising tools for automated reinforcement learning (RL) reward design, owing to their robust capabilities in commonsense reasoning an…
cs.AI2024
GFPack++: Improving 2D Irregular Packing by Learning Gradient Field with Attention
Tianyang Xue, Lin Lu, Yang Liu +5
2D irregular packing is a classic combinatorial optimization problem with various applications, such as material utilization and texture atlas generation. This NP-hard problem requ…
cs.AI2024
SocialGFs: Learning Social Gradient Fields for Multi-Agent Reinforcement Learning
Qian Long, Fangwei Zhong, Mingdong Wu +2
Multi-agent systems (MAS) need to adaptively cope with dynamic environments, changing agent populations, and diverse tasks. However, most of the multi-agent systems cannot easily h…