Fetching the paper…
Reading the bibliography…
Developing intelligent agents capable of seamless coordination with humans is a critical step towards achieving artificial general intelligence.
Efficient training of artificial neural networks for autonomous navigation
Dean Pomerleau · 1991
Earlier work this paper cites.
Markov games as a framework for multi-agent reinforcement learning
Michael L Littman · 1994
Earlier work this paper cites.
Artificial General Intelligence
Ben Goertzel and Cassio Pennachin · 2007
Earlier work this paper cites.
Fictitious self-play in extensive-form games
Johannes Heinrich, Marc Lanctot, and David Silver · 2015
Earlier work this paper cites.
Population based training of neural networks
Max Jaderberg, Valentin Dalibard, Simon Osindero, Wojciech M Czarnecki, Jeff Donahue, Ali Razavi, Oriol Vinyals, Tim Green, Iain Dunning, Karen Simonyan, et al · 2017
Earlier work this paper cites.
Reinforcement Learning: An Introduction
Richard S Sutton and Andrew G Barto · 2018
Earlier work this paper cites.
Generalization without systematicity: On the compositional skills of sequence-to-sequence recurrent networks
Brenden M. Lake and Marco Baroni · 2018
Earlier work this paper cites.
On the utility of learning about humans for human-ai coordination
Micah Carroll, Rohin Shah, Mark K. Ho, Tom Griffiths, Sanjit A. Seshia, Pieter Abbeel, and Anca D. Dragan · 2019
Earlier work this paper cites.
DROP: A reading comprehension benchmark requiring discrete reasoning over paragraphs
Dheeru Dua, Yizhong Wang, Pradeep Dasigi, Gabriel Stanovsky, Sameer Singh, and Matt Gardner · 2019
Earlier work this paper cites.
On the critical role of conventions in adaptive human-ai collaboration
Andy Shih, Arjun Sawhney, Jovana Kondic, Stefano Ermon, and Dorsa Sadigh · 2020
Earlier work this paper cites.
How to build an open-domain question answering system?
Lilian Weng · 2020
Earlier work this paper cites.
Off-belief learning
Hengyuan Hu, Adam Lerer, Brandon Cui, Luis Pineda, Noam Brown, and Jakob N. Foerster · 2021
Earlier work this paper cites.
K-level reasoning for zero-shot coordination in hanabi
Brandon Cui, Hengyuan Hu, Luis Pineda, and Jakob N. Foerster · 2021
Earlier work this paper cites.
Evaluation of human-ai teams for learned and rule-based agents in hanabi
Ho Chit Siu, Jaime Daniel Peña, Edenna Chen, Yutai Zhou, Victor J. Lopez, Kyle Palko, Kimberlee C. Chang, and Ross E. Allen · 2021
Earlier work this paper cites.
Collaborating with humans without human data
DJ Strouse, Kevin McKee, Matt Botvinick, Edward Hughes, and Richard Everett · 2021
Earlier work this paper cites.
Foundations of cognitive processes
Robert W Thatcher and E Roy John · 2021
Earlier work this paper cites.
RMIX: learning risk-sensitive policies for cooperative reinforcement learning agents
Wei Qiu, Xinrun Wang, Runsheng Yu, Rundong Wang, Xu He, Bo An, Svetlana Obraztsova, and Zinovi Rabinovich · 2021
Cited alongside, same era.
Training verifiers to solve math word problems
Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, Christopher Hesse, and John Schulman · 2021
Cited alongside, same era.
Human-ai coordination via human-regularized search and learning
Hengyuan Hu, David J. Wu, Adam Lerer, Jakob N. Foerster, and Noam Brown · 2022
Cited alongside, same era.
The boltzmann policy distribution: Accounting for systematic suboptimality in human models
Cassidy Laidlaw and Anca D. Dragan · 2022
Cited alongside, same era.
Balancing and scheduling assembly lines with human-robot collaboration tasks
Amir Nourmohammadi, Masood Fathi, and Amos H. C. Ng · 2022
Learning latent representations to co-adapt to humans
Sagar Parekh and Dylan P. Losey · 2023
Closest in time.
Learning zero-shot cooperation with humans, assuming humans are biased
Chao Yu, Jiaxuan Gao, Weilin Liu, Botian Xu, Hao Tang, Jiaqi Yang, Yu Wang, and Yi Wu · 2023
Closest in time.
Maximum entropy population-based training for zero-shot human-ai coordination
Rui Zhao, Jinming Song, Yufeng Yuan, Haifeng Hu, Yang Gao, Yi Wu, Zhongqian Sun, and Wei Yang · 2023
Closest in time.
Fast teammate adaptation in the presence of sudden policy change
Ziqian Zhang, Lei Yuan, Lihe Li, Ke Xue, Chengxing Jia, Cong Guan, Chao Qian, and Yang Yu · 2023
Closest in time.
The Impact of Artificial Intelligence on Human Rights Legislation: A Plea for an AI Convention
John-Stewart Gordon · 2023
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Human-robot-collaboration in the healthcare environment: An exploratory study
Katharina Gleichauf, Ramona Schmid, and Verena Wagner-Hartl · 2022
Cited alongside, same era.
Heterogeneous multi-agent zero-shot coordination by coevolution
Ke Xue, Yutong Wang, Lei Yuan, Cong Guan, Chao Qian, and Yang Yu · 2022
Cited alongside, same era.
Generating diverse cooperative agents by learning incompatible policies
Rujikorn Charakorn, Poramate Manoonpong, and Nat Dilokthanakul · 2022
Cited alongside, same era.
Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed H. Chi, Quoc V. Le, and Denny Zhou · 2022
Cited alongside, same era.
In situ bidirectional human-robot value alignment
Luyao Yuan, Xiaofeng Gao, Zilong Zheng, Mark Edmonds, Ying Nian Wu, Federico Rossano, Hongjing Lu, Yixin Zhu, and Song-Chun Zhu · 2022
Cited alongside, same era.
Planning with large language models via corrective re-prompting
Shreyas Sundara Raman, Vanya Cohen, Eric Rosen, Ifrah Idrees, David Paulius, and Stefanie Tellex · 2022
Cited alongside, same era.
Language models as zero-shot planners: Extracting actionable knowledge for embodied agents
Wenlong Huang, Pieter Abbeel, Deepak Pathak, and Igor Mordatch · 2022
Cited alongside, same era.
Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang, Xiaolei Wang, Yupeng Hou, Yingqian Min, Beichen Zhang, Junjie Zhang, Zican Dong, Yifan Du, Chen Yang, Yushuo Chen, Zhipeng Chen, Jinhao Jiang, Ruiyang Ren, Yifan Li, Xinyu Tang, Zikang Liu, Peiyu Liu, Jian-Yun Nie, and Ji-Rong Wen · 2023
Closest in time.
Grounded decoding: Guiding text generation with grounded models for robot control
Wenlong Huang, Fei Xia, Dhruv Shah, Danny Driess, Andy Zeng, Yao Lu, Pete Florence, Igor Mordatch, Sergey Levine, Karol Hausman, and Brian Ichter · 2023
Closest in time.
Reasoning with language model prompting: A survey
Shuofei Qiao, Yixin Ou, Ningyu Zhang, Xiang Chen, Yunzhi Yao, Shumin Deng, Chuanqi Tan, Fei Huang, and Huajun Chen · 2023
Closest in time.
Prompted llms as chatbot modules for long open-domain conversation
Gibbeum Lee, Volker Hartmann, Jongho Park, Dimitris Papailiopoulos, and Kangwook Lee · 2023
Closest in time.
Least-to-most prompting enables complex reasoning in large language models
Denny Zhou, Nathanael Schärli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Claire Cui, Olivier Bousquet, Quoc V. Le, and Ed H. Chi · 2023
Closest in time.
Siren’s song in the AI ocean: A survey on hallucination in large language models
Yue Zhang, Yafu Li, Leyang Cui, Deng Cai, Lemao Liu, Tingchen Fu, Xinting Huang, Enbo Zhao, Yu Zhang, Yulong Chen, Longyue Wang, Anh Tuan Luu, Wei Bi, Freda Shi, and Shuming Shi · 2023
Closest in time.
Semantically aligned task decomposition in multi-agent reinforcement learning
Wenhao Li, Dan Qiao, Baoxiang Wang, Xiangfeng Wang, Bo Jin, and Hongyuan Zha · 2023
Closest in time.
Proagent: Building proactive cooperative AI with large language models
Ceyao Zhang, Kaijie Yang, Siyi Hu, Zihao Wang, Guanghe Li, Yihang Sun, Cheng Zhang, Zhaowei Zhang, Anji Liu, Song-Chun Zhu, Xiaojun Chang, Junge Zhang, Feng Yin, Yitao Liang, and Yaodong Yang · 2023
Closest in time.
A survey on large language model based autonomous agents
Lei Wang, Chen Ma, Xueyang Feng, Zeyu Zhang, Hao Yang, Jingsen Zhang, Zhiyuan Chen, Jiakai Tang, Xu Chen, Yankai Lin, Wayne Xin Zhao, Zhewei Wei, and Ji-Rong Wen · 2023
Closest in time.
The rise and potential of large language model based agents: A survey
Zhiheng Xi, Wenxiang Chen, Xin Guo, Wei He, Yiwen Ding, Boyang Hong, Ming Zhang, Junzhe Wang, Senjie Jin, Enyu Zhou, Rui Zheng, Xiaoran Fan, Xiao Wang, Limao Xiong, Yuhao Zhou, Weiran Wang, Changhao Jiang, Yicheng Zou, Xiangyang Liu, Zhangyue Yin, Shihan Dou, Rongxiang Weng, Wensen Cheng, Qi Zhang, Wenjuan Qin, Yongyan Zheng, Xipeng Qiu, Xuanjing Huan, and Tao Gui · 2023
Closest in time.
Role-play with large language models
Murray Shanahan, Kyle McDonell, and Laria Reynolds · 2023
Closest in time.