arXivDaily arXiv每日学术速递 周一至周五更新

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智能体、工具调用、规划、工作流、多智能体和自主任务执行。

共收录 5059 信号源:cs.AI, cs.CL, cs.LG, cs.SE

1. 工具调用 5059 篇

1802.04697 2018-07-18 cs.AI cs.LG stat.ML 62%

Learning to Search with MCTSnets

Arthur Guez, Théophane Weber, Ioannis Antonoglou, Karen Simonyan, Oriol Vinyals, Daan Wierstra, Rémi Munos, David Silver

专题命中 工具调用 :planning(abstract);分类 cs.AI、cs.LG

Comments ICML 2018 (camera-ready version)

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1806.02448 2018-06-08 cs.LG cs.AI cs.NE stat.ML 62%

Deep Reinforcement Learning for General Video Game AI

Ruben Rodriguez Torrado, Philip Bontrager, Julian Togelius, Jialin Liu, Diego Perez-Liebana

专题命中 工具调用 :planning(abstract);分类 cs.AI、cs.LG

Comments 8 pages, 4 figures, Accepted at the conference on Computational Intelligence and Games 2018 IEEE

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1709.00503 2018-05-24 stat.ML cs.AI cs.LG 62%

Mean Actor Critic

Cameron Allen, Kavosh Asadi, Melrose Roderick, Abdel-rahman Mohamed, George Konidaris, Michael Littman

专题命中 工具调用 :agent(abstract);分类 cs.AI、cs.LG

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1803.10937 2018-03-30 cs.LG cs.AI stat.ML 62%

Best arm identification in multi-armed bandits with delayed feedback

Aditya Grover, Todor Markov, Peter Attia, Norman Jin, Nicholas Perkins, Bryan Cheong, Michael Chen, Zi Yang, Stephen Harris, William Chueh, Stefano Ermon

专题命中 工具调用 :agent(abstract);分类 cs.AI、cs.LG

Comments AISTATS 2018

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1803.08456 2018-03-23 cs.AI cs.LG stat.ML 62%

Deep Reinforcement Learning with Model Learning and Monte Carlo Tree Search in Minecraft

Stephan Alaniz

专题命中 工具调用 :agent(abstract);分类 cs.AI、cs.LG

Comments The 3rd Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM) 2017

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1707.04873 2017-11-22 cs.LG cs.AI 62%

Efficient Architecture Search by Network Transformation

Han Cai, Tianyao Chen, Weinan Zhang, Yong Yu, Jun Wang

专题命中 工具调用 :agent(abstract);分类 cs.AI、cs.LG

Comments The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18). We change the title from "Reinforcement Learning for Architecture Search by Network Transformation" to "Efficient Architecture Search by Network Transformation"

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1711.01391 2017-11-08 cs.AI cs.LG cs.RO 62%

Guiding the search in continuous state-action spaces by learning an action sampling distribution from off-target samples

Beomjoon Kim, Leslie Pack Kaelbling, Tomas Lozano-Perez

专题命中 工具调用 :planning(abstract);分类 cs.AI、cs.LG

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1710.05958 2017-10-18 cs.LG cs.AI cs.CV 62%

Gradient-free Policy Architecture Search and Adaptation

Sayna Ebrahimi, Anna Rohrbach, Trevor Darrell

专题命中 工具调用 :agent(abstract);分类 cs.AI、cs.LG

Comments Accepted in Conference on Robot Learning, 2017

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1707.03034 2017-07-12 cs.RO cs.AI cs.LG 62%

Learning Heuristic Search via Imitation

Mohak Bhardwaj, Sanjiban Choudhury, Sebastian Scherer

专题命中 工具调用 :planning(abstract);分类 cs.AI、cs.LG

Comments 14 pages

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1705.08520 2017-05-25 cs.AI cs.LG cs.NE 62%

An effective algorithm for hyperparameter optimization of neural networks

Gonzalo Diaz, Achille Fokoue, Giacomo Nannicini, Horst Samulowitz

专题命中 工具调用 :tool use(abstract);分类 cs.AI、cs.LG

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1609.00777 2017-04-21 cs.CL cs.LG 62%

Towards End-to-End Reinforcement Learning of Dialogue Agents for Information Access

Bhuwan Dhingra, Lihong Li, Xiujun Li, Jianfeng Gao, Yun-Nung Chen, Faisal Ahmed, Li Deng

专题命中 工具调用 :agent(abstract);分类 cs.CL、cs.LG

Comments Accepted at ACL 2017

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1610.00388 2017-01-12 cs.CL cs.LG 62%

Learning to Translate in Real-time with Neural Machine Translation

Jiatao Gu, Graham Neubig, Kyunghyun Cho, Victor O. K. Li

专题命中 工具调用 :agent(abstract);分类 cs.CL、cs.LG

Comments 10 pages, camera ready

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1509.01644 2015-11-30 cs.AI cs.LG 62%

Reinforcement Learning with Parameterized Actions

Warwick Masson, Pravesh Ranchod, George Konidaris

专题命中 工具调用 :agent(abstract);分类 cs.AI、cs.LG

Comments Accepted for AAAI 2016

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1205.3109 2015-03-19 cs.LG cs.AI stat.ML 62%

Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based Search

Arthur Guez, David Silver, Peter Dayan

专题命中 工具调用 :planning(abstract);分类 cs.AI、cs.LG

Comments 14 pages, 7 figures, includes supplementary material. Advances in Neural Information Processing Systems (NIPS) 2012

Journal ref (2012) Advances in Neural Information Processing Systems 25, pages 1034-1042

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1306.4753 2013-06-21 cs.LG cs.AI math.OC 62%

Galerkin Methods for Complementarity Problems and Variational Inequalities

Geoffrey J. Gordon

专题命中 工具调用 :planning(abstract);分类 cs.AI、cs.LG

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1209.3818 2013-04-03 cs.AI cs.LG 62%

Evolution and the structure of learning agents

Alok Raj

专题命中 工具调用 :agent(abstract);分类 cs.AI、cs.LG

Comments total 4 pages. Submitted to IEEE Congress on Evolutionary Computation 2013

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1301.5488 2013-01-24 cs.LG cs.AI stat.ML 62%

Multi-class Generalized Binary Search for Active Inverse Reinforcement Learning

Francisco Melo, Manuel Lopes

专题命中 工具调用 :agent(abstract);分类 cs.AI、cs.LG

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1202.2112 2012-02-10 cs.AI cs.LG cs.RO 62%

Predicting Contextual Sequences via Submodular Function Maximization

Debadeepta Dey, Tian Yu Liu, Martial Hebert, J. Andrew Bagnell

专题命中 工具调用 :planning(abstract);分类 cs.AI、cs.LG

Comments 8 pages

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0909.0801 2010-12-30 cs.AI cs.IT cs.LG math.IT 62%

A Monte Carlo AIXI Approximation

Joel Veness, Kee Siong Ng, Marcus Hutter, William Uther, David Silver

专题命中 工具调用 :agent(abstract);分类 cs.AI、cs.LG

Comments 51 LaTeX pages, 11 figures, 6 tables, 4 algorithms

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0912.5029 2010-01-14 cs.LG cs.AI 62%

Complexity of stochastic branch and bound methods for belief tree search in Bayesian reinforcement learning

Christos Dimitrakakis

专题命中 工具调用 :planning(abstract);分类 cs.AI、cs.LG

Comments 13 pages, 1 figure, ICAART 2010

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cs/0610170 2009-12-01 cs.LG cs.AI 62%

Low-complexity modular policies: learning to play Pac-Man and a new framework beyond MDPs

Istvan Szita, Andras Lorincz

专题命中 工具调用 :agent(abstract);分类 cs.AI、cs.LG

Comments 23 pages

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2608.15089 2026-08-18 cs.AI 新提交 61%

StateM: Reaching 95.3% Raw Accuracy, or a \$15 Frontier Run, on Terminal-Bench 2.1 via Harness Scaling

StateM:通过工具链扩展在Terminal-Bench 2.1上达到95.3%的原始准确率,或实现15美元的前沿运行

Ziheng Qin, Yaxin Lu, Zhangyang Atlas Wang, Kai Wang

专题命中 工具调用 :agent(abstract,comments);分类 cs.AI

AI总结 本研究提出智能体原生运行时StateM,通过工具链扩展优化智能体执行系统,在Terminal-Bench 2.1等基准上显著提升GPT-5.6、DeepSeek-V4 Flash等模型的任务准确率,大幅降低运行成本,验证了其有效性与泛化性。

Comments Harness Scaling, Semi-Self-Evolving Agent

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2604.07872 2026-04-10 cs.NE cs.AI 61%

PyVRP$^+$: LLM-Driven Metacognitive Heuristic Evolution for Hybrid Genetic Search in Vehicle Routing Problems

PyVRP$^+$:基于LLM的元认知启发式进化方法用于车辆路径问题中的混合遗传搜索

Manuj Malik, Jianan Zhou, Shashank Reddy Chirra, Zhiguang Cao

机构 * Singapore Management University(新加坡管理大学) Nanyang Technological University(南洋理工大学) University of Oxford(牛津大学)

专题命中 工具调用 :agent(abstract);分类 cs.AI;autonomous agent(comments)

AI总结 本文提出PyVRP$^+$,通过LLM驱动的元认知启发式进化方法改进混合遗传搜索算法,发现更高效的启发式策略,提升VRP问题的求解性能。

Comments 18 pages, accepted to the 25th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2026)

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2602.17675 2026-02-23 cs.DC cs.AI 61%

Mind the Boundary: Stabilizing Gemini Enterprise A2A via a Cloud Run Hub Across Projects and Accounts

注意边界:通过跨项目和账户的云运行枢纽稳定Gemini Enterprise A2A

Takao Morita

机构 * Independent Researcher(独立研究者)

专题命中 工具调用 :agent(abstract,comments);分类 cs.AI

AI总结 通过跨项目和账户的云运行枢纽稳定Gemini Enterprise A2A,解决边界依赖认证和UI兼容性问题,实现可靠路由和稳定响应。

Comments 7 pages. Implementation and evaluation study of cross-boundary agent orchestration for Gemini Enterprise UI

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2309.10796 2025-02-25 cs.RO cs.AI 61%

Heuristic Search for Path Finding with Refuelling

Shizhe Zhao, Anushtup Nandy, Howie Choset, Sivakumar Rathinam, Zhongqiang Ren

专题命中 工具调用 :planning(abstract,comments);分类 cs.AI

Comments 8 pages, 6 figures, RA-L 2025 submission, Motion and Path Path Planning, Scheduling and Coordination, Robotics in Under-Resourced Settings

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2306.04019 2023-06-08 cs.AI 61%

Learning Search-Space Specific Heuristics Using Neural Networks

Yu Liu, Ryo Kuroiwa, Alex Fukunaga

专题命中 工具调用 :planning(abstract,comments);分类 cs.AI

Comments Proceedings of ICAPS Workshop on Heuristics and Search for Domain-independent Planning (HSDIP) 2020, pp.1-8

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1706.03254 2017-11-13 cs.AI cs.DC 61%

On Hash-Based Work Distribution Methods for Parallel Best-First Search

Yuu Jinnai, Alex Fukunaga

专题命中 工具调用 :planning(abstract,comments);分类 cs.AI

Comments Source code of domain-specific solvers in multicore environment: https://github.com/jinnaiyuu/Parallel-Best-First-Searches Source code of classical planning in distributed environment: https://github.com/jinnaiyuu/distributed-fast-downward

Journal ref Yuu Jinnai and Alex Fukunaga. (2017). On Hash-Based Work Distribution Methods for Parallel Best-First Search. Journal of Artificial Intelligence Research (JAIR), 60, 491-548

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2309.12589 2023-09-25 cs.RO 60%

A Multi-Robot Task Assignment Framework for Search and Rescue with Heterogeneous Teams

Hamid Osooli, Paul Robinette, Kshitij Jerath, S. Reza Ahmadzadeh

专题命中 工具调用 :planning(abstract);agent(comments);multi-agent(comments)

Comments The 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2023 Advances in Multi-Agent Learning - Coordination, Perception, and Control Workshop)

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2608.18727 2026-08-20 cs.LG cs.IR 新提交 57%

Visual-Aware Representation of Web Pages for Machine Learning Applications

面向机器学习应用的网页视觉感知表示

Radek Burget, Radek Hranický

机构 * Brno University of Technology(布尔诺理工大学) Faculty of Information Technology(信息技术学院)

专题命中 工具调用 :workflow(abstract);分类 cs.LG

AI总结 本文提出基于FitLayout的网页视觉感知表示与机器学习平台,支持数据集准备、机器学习输入获取,可用于训练图神经网络识别网页关键内容元素,保障结果可复现。

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2608.17546 2026-08-19 cs.SE 新提交 57%

REST API Testing with Verified LLM-Inferred Dependencies and Response-Driven Refinement

基于经验证的LLM推断依赖关系与响应驱动优化的REST API测试

Tu Nguyen, Thanh Nguyen, Huy Nguyen, Viet Nguyen, Tien N. Nguyen, Vu Nguyen

专题命中 工具调用 :workflow(abstract);分类 cs.SE

AI总结 本文提出APIPilot框架,通过执行验证LLM推断的REST API依赖关系,结合响应驱动优化,在16个真实API上实现高覆盖率与成功率,优于现有基线。

Comments Submitted to ICSE 2027

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