Guardado en:
| Autores principales: | Qian, Yiyu, Zhao, Liyuan, Miller, Tim |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2604.14687 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Exploring Explainable Multi-agent MCTS-minimax Hybrids in Board Game Using Process Mining
por: Qian, Yiyu, et al.
Publicado: (2025)
por: Qian, Yiyu, et al.
Publicado: (2025)
Combining LLMs with Logic-Based Framework to Explain MCTS
por: An, Ziyan, et al.
Publicado: (2025)
por: An, Ziyan, et al.
Publicado: (2025)
M$^2$-Miner: Multi-Agent Enhanced MCTS for Mobile GUI Agent Data Mining
por: Lv, Rui, et al.
Publicado: (2026)
por: Lv, Rui, et al.
Publicado: (2026)
COMPASS: Cognitive MCTS-Guided Process Alignment for Safe Search Agents
por: Shen, Wenkai, et al.
Publicado: (2026)
por: Shen, Wenkai, et al.
Publicado: (2026)
MASTER: A Multi-Agent System with LLM Specialized MCTS
por: Gan, Bingzheng, et al.
Publicado: (2025)
por: Gan, Bingzheng, et al.
Publicado: (2025)
Navigating the Alpha Jungle: An LLM-Powered MCTS Framework for Formulaic Factor Mining
por: Shi, Yu, et al.
Publicado: (2025)
por: Shi, Yu, et al.
Publicado: (2025)
An Evolutionary Framework for Connect-4 as Test-Bed for Comparison of Advanced Minimax, Q-Learning and MCTS
por: Taylor, Henry, et al.
Publicado: (2024)
por: Taylor, Henry, et al.
Publicado: (2024)
TriEx: A Game-based Tri-View Framework for Explaining Internal Reasoning in Multi-Agent LLMs
por: Wang, Ziyi, et al.
Publicado: (2026)
por: Wang, Ziyi, et al.
Publicado: (2026)
ChatSOP: An SOP-Guided MCTS Planning Framework for Controllable LLM Dialogue Agents
por: Li, Zhigen, et al.
Publicado: (2024)
por: Li, Zhigen, et al.
Publicado: (2024)
MAO: A Framework for Process Model Generation with Multi-Agent Orchestration
por: Lin, Leilei, et al.
Publicado: (2024)
por: Lin, Leilei, et al.
Publicado: (2024)
Empirical-MCTS: Continuous Agent Evolution via Dual-Experience Monte Carlo Tree Search
por: Lu, Hao, et al.
Publicado: (2026)
por: Lu, Hao, et al.
Publicado: (2026)
Exploring Adaptive MCTS with TD Learning in miniXCOM
por: Saadat, Kimiya, et al.
Publicado: (2022)
por: Saadat, Kimiya, et al.
Publicado: (2022)
Explaining Fine Tuned LLMs via Counterfactuals A Knowledge Graph Driven Framework
por: Wang, Yucheng, et al.
Publicado: (2025)
por: Wang, Yucheng, et al.
Publicado: (2025)
Know Your Intent: An Autonomous Multi-Perspective LLM Agent Framework for DeFi User Transaction Intent Mining
por: Mao, Qian'ang, et al.
Publicado: (2025)
por: Mao, Qian'ang, et al.
Publicado: (2025)
Boosting MCTS with Free Energy Minimization
por: Dao, Mawaba Pascal, et al.
Publicado: (2025)
por: Dao, Mawaba Pascal, et al.
Publicado: (2025)
Explaining Decentralized Multi-Agent Reinforcement Learning Policies
por: Boggess, Kayla, et al.
Publicado: (2025)
por: Boggess, Kayla, et al.
Publicado: (2025)
A Tale of LLMs and Induced Small Proxies: Scalable Agents for Knowledge Mining
por: Zhang, Sipeng, et al.
Publicado: (2025)
por: Zhang, Sipeng, et al.
Publicado: (2025)
CodeAgents: A Token-Efficient Framework for Codified Multi-Agent Reasoning in LLMs
por: Yang, Bruce, et al.
Publicado: (2025)
por: Yang, Bruce, et al.
Publicado: (2025)
Where Common Knowledge Cannot Be Formed, Common Belief Can -- Planning with Multi-Agent Belief Using Group Justified Perspectives
por: Hu, Guang, et al.
Publicado: (2024)
por: Hu, Guang, et al.
Publicado: (2024)
Lessons Learned: A Multi-Agent Framework for Code LLMs to Learn and Improve
por: Liu, Yuanzhe, et al.
Publicado: (2025)
por: Liu, Yuanzhe, et al.
Publicado: (2025)
Re-Thinking Process Mining in the AI-Based Agents Era
por: Berti, Alessandro, et al.
Publicado: (2024)
por: Berti, Alessandro, et al.
Publicado: (2024)
MUSE: MCTS-Driven Red Teaming Framework for Enhanced Multi-Turn Dialogue Safety in Large Language Models
por: Yan, Siyu, et al.
Publicado: (2025)
por: Yan, Siyu, et al.
Publicado: (2025)
IG-MCTS: Human-in-the-Loop Cooperative Navigation under Incomplete Information
por: Chen, Shenghui, et al.
Publicado: (2025)
por: Chen, Shenghui, et al.
Publicado: (2025)
FREESON: Retriever-Free Retrieval-Augmented Reasoning via Corpus-Traversing MCTS
por: Kim, Chaeeun, et al.
Publicado: (2025)
por: Kim, Chaeeun, et al.
Publicado: (2025)
PAC-MCTS: Bias-Aware Pruning for Robust LLM-Guided Search and Planning
por: Qian, Tianhao
Publicado: (2026)
por: Qian, Tianhao
Publicado: (2026)
COS(M+O)S: Curiosity and RL-Enhanced MCTS for Exploring Story Space via Language Models
por: Materzok, Tobias
Publicado: (2025)
por: Materzok, Tobias
Publicado: (2025)
RPM-MCTS: Knowledge-Retrieval as Process Reward Model with Monte Carlo Tree Search for Code Generation
por: Lin, Yuanyuan, et al.
Publicado: (2025)
por: Lin, Yuanyuan, et al.
Publicado: (2025)
Structure and Reduction of MCTS for Explainable-AI
por: Bustin, Ronit, et al.
Publicado: (2024)
por: Bustin, Ronit, et al.
Publicado: (2024)
Automating Skill Acquisition through Large-Scale Mining of Open-Source Agentic Repositories: A Framework for Multi-Agent Procedural Knowledge Extraction
por: Bi, Shuzhen, et al.
Publicado: (2026)
por: Bi, Shuzhen, et al.
Publicado: (2026)
A Framework for Analyzing Abnormal Emergence in Service Ecosystems Through LLM-based Agent Intention Mining
por: Shen, Yifan, et al.
Publicado: (2025)
por: Shen, Yifan, et al.
Publicado: (2025)
Hierarchical Reinforcement Learning for Optimal Agent Grouping in Cooperative Systems
por: Hu, Liyuan
Publicado: (2025)
por: Hu, Liyuan
Publicado: (2025)
PMAx: An Agentic Framework for AI-Driven Process Mining
por: Antonov, Anton, et al.
Publicado: (2026)
por: Antonov, Anton, et al.
Publicado: (2026)
Multi-Agent Influence Diagrams to Hybrid Threat Modeling
por: Vonk, Maarten C., et al.
Publicado: (2026)
por: Vonk, Maarten C., et al.
Publicado: (2026)
MCTS-SQL: Light-Weight LLMs can Master the Text-to-SQL through Monte Carlo Tree Search
por: Yuan, Shuozhi, et al.
Publicado: (2025)
por: Yuan, Shuozhi, et al.
Publicado: (2025)
XAgents: A Unified Framework for Multi-Agent Cooperation via IF-THEN Rules and Multipolar Task Processing Graph
por: Yang, Hailong, et al.
Publicado: (2025)
por: Yang, Hailong, et al.
Publicado: (2025)
Tracing the Roots: A Multi-Agent Framework for Uncovering Data Lineage in Post-Training LLMs
por: Li, Yu, et al.
Publicado: (2026)
por: Li, Yu, et al.
Publicado: (2026)
HealthProcessAI: A Technical Framework and Proof-of-Concept for LLM-Enhanced Healthcare Process Mining
por: Illueca-Fernandez, Eduardo, et al.
Publicado: (2025)
por: Illueca-Fernandez, Eduardo, et al.
Publicado: (2025)
Integrating Counterfactual Simulations with Language Models for Explaining Multi-Agent Behaviour
por: Gyevnár, Bálint, et al.
Publicado: (2025)
por: Gyevnár, Bálint, et al.
Publicado: (2025)
Speeding Up Path Planning via Reinforcement Learning in MCTS for Automated Parking
por: Zheng, Xinlong, et al.
Publicado: (2024)
por: Zheng, Xinlong, et al.
Publicado: (2024)
Automated Large-scale CVRP Solver Design via LLM-assisted Flexible MCTS
por: Guo, Tong, et al.
Publicado: (2026)
por: Guo, Tong, et al.
Publicado: (2026)
Ejemplares similares
-
Exploring Explainable Multi-agent MCTS-minimax Hybrids in Board Game Using Process Mining
por: Qian, Yiyu, et al.
Publicado: (2025) -
Combining LLMs with Logic-Based Framework to Explain MCTS
por: An, Ziyan, et al.
Publicado: (2025) -
M$^2$-Miner: Multi-Agent Enhanced MCTS for Mobile GUI Agent Data Mining
por: Lv, Rui, et al.
Publicado: (2026) -
COMPASS: Cognitive MCTS-Guided Process Alignment for Safe Search Agents
por: Shen, Wenkai, et al.
Publicado: (2026) -
MASTER: A Multi-Agent System with LLM Specialized MCTS
por: Gan, Bingzheng, et al.
Publicado: (2025)