1 citations · 7 across the 57 of their papers we have counts for
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Self-supervised Hierarchical Visual Reasoning with World Model
Yuanfei Xu, Lin Liu, Wengang Zhou +2
3D open-world environments with adversarial opponents remain a core challenge for reinforcement learning due to their vast state spaces. Effective reasoning representations are ess…
SGA-MCTS: Decoupling Planning from Execution via Training-Free Atomic Experience Retrieval
Xin Xie, Dongyun Xue, Wuguannan Yao +5
LLM-powered systems require complex multi-step decision-making abilities to solve real-world tasks, yet current planning approaches face a trade-off between the high latency of inf…
Search-Based Credit Assignment for Offline Preference-Based Reinforcement Learning
Xiancheng Gao, Yufeng Shi, Wengang Zhou +1
Offline reinforcement learning refers to the process of learning policies from fixed datasets, without requiring additional environment interaction. However, it often relies on wel…
Model Evolution Framework with Genetic Algorithm for Multi-Task Reinforcement Learning
Yan Yu, Wengang Zhou, Yaodong Yang +3
Multi-task reinforcement learning employs a single policy to complete various tasks, aiming to develop an agent with generalizability across different scenarios. Given the shared c…
RL-LLM-DT: An Automatic Decision Tree Generation Method Based on RL Evaluation and LLM Enhancement
Junjie Lin, Jian Zhao, Lin Liu +6
Traditionally, AI development for two-player zero-sum games has relied on two primary techniques: decision trees and reinforcement learning (RL). A common approach involves using a…
DanZero+: Dominating the GuanDan Game through Reinforcement Learning
Youpeng Zhao, Yudong Lu, Jian Zhao +2
The utilization of artificial intelligence (AI) in card games has been a well-explored subject within AI research for an extensive period. Recent advancements have propelled AI pro…