AI Agent - arXivDaily 专题

2304.14698 2023-05-01 cs.LG cs.AI 62%

X-RLflow: Graph Reinforcement Learning for Neural Network Subgraphs Transformation

Guoliang He, Sean Parker, Eiko Yoneki

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

Comments MLSys 2023

2303.13228 2023-03-24 cs.LG cs.AI cs.SY eess.SY stat.ML 62%

Enriching Neural Network Training Dataset to Improve Worst-Case Performance Guarantees

Rahul Nellikkath, Spyros Chatzivasileiadis

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

Comments arXiv admin note: text overlap with arXiv:2212.10930

2303.10182 2023-03-21 cs.LG cs.AI cs.NE 62%

SFE: A Simple, Fast and Efficient Feature Selection Algorithm for High-Dimensional Data

Behrouz Ahadzadeh, Moloud Abdar, Fatemeh Safara, Abbas Khosravi, Mohammad Bagher Menhaj, Ponnuthurai Nagaratnam Suganthan

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

2302.07940 2023-02-17 cs.RO cs.AI cs.LG 62%

Online Tool Selection with Learned Grasp Prediction Models

Khashayar Rohanimanesh, Jake Metzger, William Richards, Aviv Tamar

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

Comments 14 pages (including the cover page), 5 Figures, Technical Report, OSARO Inc

2207.12805 2023-02-03 q-bio.QM cs.AI cs.LG q-bio.GN 62%

Neural Design for Genetic Perturbation Experiments

Aldo Pacchiano, Drausin Wulsin, Robert A. Barton, Luis Voloch

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

Comments 22 pages main, 15 pages appendix

2205.13134 2023-02-03 cs.AI cs.LG cs.SC nlin.CD physics.comp-ph 62%

Symbolic Physics Learner: Discovering governing equations via Monte Carlo tree search

Fangzheng Sun, Yang Liu, Jian-Xun Wang, Hao Sun

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

Comments 22 pages

Journal ref ICLR 2023

2211.10688 2023-01-24 cs.CL cs.AI 62%

ReInform: Selecting paths with reinforcement learning for contextualized link prediction

Marina Speranskaya, Sameh Methias, Benjamin Roth

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

2212.03978 2023-01-12 cs.LG cs.AI 62%

Learning Graph Search Heuristics

Michal Pándy, Weikang Qiu, Gabriele Corso, Petar Veličković, Rex Ying, Jure Leskovec, Pietro Liò

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

2212.11083 2023-01-03 cs.LG cs.AI cs.IT math.IT 62%

Adapting the Exploration Rate for Value-of-Information-Based Reinforcement Learning

Isaac J. Sledge, Jose C. Principe

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

Comments Submitted to the IEEE Transactions on Information Theory

2212.14849 2023-01-02 cs.LG cs.AI 62%

Symbolic Visual Reinforcement Learning: A Scalable Framework with Object-Level Abstraction and Differentiable Expression Search

Wenqing Zheng, S P Sharan, Zhiwen Fan, Kevin Wang, Yihan Xi, Zhangyang Wang

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

2205.10124 2022-12-28 cs.AI astro-ph.EP astro-ph.IM cs.LG 62%

The Fellowship of the Dyson Ring: ACT&Friends' Results and Methods for GTOC 11

Marcus Märtens, Dario Izzo, Emmanuel Blazquez, Moritz von Looz, Pablo Gómez, Anne Mergy, Giacomo Acciarini, Chit Hong Yam, Javier Hernando Ayuso, Yuri Shimane

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

2212.11730 2022-12-23 cs.AI cs.LG 62%

TransPath: Learning Heuristics For Grid-Based Pathfinding via Transformers

Daniil Kirilenko, Anton Andreychuk, Aleksandr Panov, Konstantin Yakovlev

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

Comments Pre-print of the paper accepted to AAAI'23

2211.12615 2022-11-24 cs.CL cs.AI 62%

AutoReply: Detecting Nonsense in Dialogue Introspectively with Discriminative Replies

Weiyan Shi, Emily Dinan, Adi Renduchintala, Daniel Fried, Athul Paul Jacob, Zhou Yu, Mike Lewis

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

2211.06721 2022-11-15 cs.LG cs.AI 62%

Using Features at Multiple Temporal and Spatial Resolutions to Predict Human Behavior in Real Time

Liang Zhang, Justin Lieffers, Adarsh Pyarelal

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

Comments Presented at AAAI Fall 2021 Symposium on ToM for Teams, to be published as a chapter in a Springer volume

2211.03769 2022-11-08 cs.AI cs.LG cs.RO 62%

Are AlphaZero-like Agents Robust to Adversarial Perturbations?

Li-Cheng Lan, Huan Zhang, Ti-Rong Wu, Meng-Yu Tsai, I-Chen Wu, Cho-Jui Hsieh

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

Comments Accepted by Neurips 2022

2206.08569 2022-10-19 cs.LG cs.AI cs.RO 62%

Bootstrapped Transformer for Offline Reinforcement Learning

Kerong Wang, Hanye Zhao, Xufang Luo, Kan Ren, Weinan Zhang, Dongsheng Li

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

Comments Accepted in NeurIPS 2022

2103.06846 2022-10-12 cs.LG cs.AI cs.NE 62%

Policy Search with Rare Significant Events: Choosing the Right Partner to Cooperate with

Paul Ecoffet, Nicolas Fontbonne, Jean-Baptiste André, Nicolas Bredeche

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

2210.05125 2022-10-12 cs.AI cs.LG cs.MA 62%

Human-AI Coordination via Human-Regularized Search and Learning

Hengyuan Hu, David J Wu, Adam Lerer, Jakob Foerster, Noam Brown

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

2109.08548 2022-10-12 cs.DC cs.AI cs.LG cs.PF cs.SY eess.SY 62%

Load Balancing in Compute Clusters with Delayed Feedback

Anam Tahir, Bastian Alt, Amr Rizk, Heinz Koeppl

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

Comments Accepted at IEEE Transactions on Computers 2022

2111.06266 2022-09-21 cs.LG cs.AI 62%

AlphaDDA: Strategies for Adjusting the Playing Strength of a Fully Trained AlphaZero System to a Suitable Human Training Partner

Kazuhisa Fujita

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

Comments 24 pages, 10 figures

2209.05206 2022-09-13 cs.LG cs.AI 62%

A Differentiable Loss Function for Learning Heuristics in A*

Leah Chrestien, Tomas Pevny, Antonin Komenda, Stefan Edelkamp

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

Comments 10 pages

2208.12878 2022-08-30 cs.LG cs.AI cs.CR 62%

DETERRENT: Detecting Trojans using Reinforcement Learning

Vasudev Gohil, Satwik Patnaik, Hao Guo, Dileep Kalathil, Jeyavijayan, Rajendran

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

Comments Published in 2022 Design Automation Conference (DAC)

2208.11535 2022-08-25 cs.LG cs.AI 62%

A model-based approach to meta-Reinforcement Learning: Transformers and tree search

Brieuc Pinon, Jean-Charles Delvenne, Raphaël Jungers

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

2208.08552 2022-08-19 cs.AI cs.HC cs.LG cs.LO 62%

A Framework for Understanding and Visualizing Strategies of RL Agents

Pedro Sequeira, Daniel Elenius, Jesse Hostetler, Melinda Gervasio

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

2208.06894 2022-08-16 cs.CV cs.AI cs.LG 62%

The SVD of Convolutional Weights: A CNN Interpretability Framework

Brenda Praggastis, Davis Brown, Carlos Ortiz Marrero, Emilie Purvine, Madelyn Shapiro, Bei Wang

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

2206.13396 2022-08-11 cs.CV cs.AI cs.LG cs.RO 62%

A Simple Approach for Visual Rearrangement: 3D Mapping and Semantic Search

Brandon Trabucco, Gunnar Sigurdsson, Robinson Piramuthu, Gaurav S. Sukhatme, Ruslan Salakhutdinov

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

Comments Winner of the Rearrangement Challenge at CVPR 2022

2012.11293 2022-08-08 cs.LG cs.AI physics.chem-ph 62%

Curiosity in exploring chemical space: Intrinsic rewards for deep molecular reinforcement learning

Luca A. Thiede, Mario Krenn, AkshatKumar Nigam, Alan Aspuru-Guzik

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

Comments 9 pages, 2 figures; comments welcome

Journal ref Machine Learning: Science and Technology 3, 035008 (2022)

2207.14722 2022-08-01 cs.LG cs.AI 62%

Automatic Reward Design via Learning Motivation-Consistent Intrinsic Rewards

Yixiang Wang, Yujing Hu, Feng Wu, Yingfeng Chen

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

2207.14140 2022-07-29 cs.LG cs.AI 62%

Playing a 2D Game Indefinitely using NEAT and Reinforcement Learning

Jerin Paul Selvan, Pravin S. Game

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

Comments 5 pages, 7 figures, 3 tables

2207.10342 2022-07-29 cs.CL cs.AI 62%

Language Model Cascades

David Dohan, Winnie Xu, Aitor Lewkowycz, Jacob Austin, David Bieber, Raphael Gontijo Lopes, Yuhuai Wu, Henryk Michalewski, Rif A. Saurous, Jascha Sohl-dickstein, Kevin Murphy, Charles Sutton

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

Comments Presented as spotlight at the Beyond Bases workshop at ICML 2022 (https://beyond-bayes.github.io)

1. 工具调用 5059 篇

X-RLflow: Graph Reinforcement Learning for Neural Network Subgraphs Transformation

Enriching Neural Network Training Dataset to Improve Worst-Case Performance Guarantees

SFE: A Simple, Fast and Efficient Feature Selection Algorithm for High-Dimensional Data

Online Tool Selection with Learned Grasp Prediction Models

Neural Design for Genetic Perturbation Experiments

Symbolic Physics Learner: Discovering governing equations via Monte Carlo tree search

ReInform: Selecting paths with reinforcement learning for contextualized link prediction

Learning Graph Search Heuristics

Adapting the Exploration Rate for Value-of-Information-Based Reinforcement Learning

Symbolic Visual Reinforcement Learning: A Scalable Framework with Object-Level Abstraction and Differentiable Expression Search

The Fellowship of the Dyson Ring: ACT&Friends' Results and Methods for GTOC 11

TransPath: Learning Heuristics For Grid-Based Pathfinding via Transformers

AutoReply: Detecting Nonsense in Dialogue Introspectively with Discriminative Replies

Using Features at Multiple Temporal and Spatial Resolutions to Predict Human Behavior in Real Time

Are AlphaZero-like Agents Robust to Adversarial Perturbations?

Bootstrapped Transformer for Offline Reinforcement Learning

Policy Search with Rare Significant Events: Choosing the Right Partner to Cooperate with

Human-AI Coordination via Human-Regularized Search and Learning

Load Balancing in Compute Clusters with Delayed Feedback

AlphaDDA: Strategies for Adjusting the Playing Strength of a Fully Trained AlphaZero System to a Suitable Human Training Partner

A Differentiable Loss Function for Learning Heuristics in A*

DETERRENT: Detecting Trojans using Reinforcement Learning

A model-based approach to meta-Reinforcement Learning: Transformers and tree search

A Framework for Understanding and Visualizing Strategies of RL Agents

The SVD of Convolutional Weights: A CNN Interpretability Framework

A Simple Approach for Visual Rearrangement: 3D Mapping and Semantic Search

Curiosity in exploring chemical space: Intrinsic rewards for deep molecular reinforcement learning

Automatic Reward Design via Learning Motivation-Consistent Intrinsic Rewards

Playing a 2D Game Indefinitely using NEAT and Reinforcement Learning

Language Model Cascades