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Achieving Artificial General Intelligence (AGI) requires AI agents that can not only make stratigic decisions but also engage in flexible and meaningful communication.
Dota 2 with large scale deep reinforcement learning
Christopher Berner, Greg Brockman, Brooke Chan, Vicki Cheung, Przemysław Dębiak, Christy Dennison, David Farhi, Quirin Fischer, Shariq Hashme, Chris Hesse, et al. 2019 · 1912
Earlier work this paper cites.
Philosophical Investigations
Ludwig Wittgenstein. 1953 · 1953
Earlier work this paper cites.
Wittgenstein and artificial intelligence
Rom Harre. 1988 · 1988
Earlier work this paper cites.
Intelligent agents: Theory and practice
Michael Wooldridge and Nicholas R Jennings. 1995 · 1995
Earlier work this paper cites.
Trueskill™: a bayesian skill rating system
Ralf Herbrich, Tom Minka, and Thore Graepel. 2006 · 2006
Earlier work this paper cites.
Philosophy and pragmatics: A language-game with ludwig wittgenstein
Roman Kopytko. 2007 · 2007
Earlier work this paper cites.
Mastering the game of go with deep neural networks and tree search
David Silver, Aja Huang, Chris J Maddison, Arthur Guez, Laurent Sifre, George Van Den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Veda Panneershelvam, Marc Lanctot, et al. 2016 · 2016
Earlier work this paper cites.
Learning language games through interaction
Sida I Wang, Percy Liang, and Christopher D Manning. 2016 · 2016
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 · 2017
Earlier work this paper cites.
Mastering the game of go without human knowledge
David Silver, Julian Schrittwieser, Karen Simonyan, Ioannis Antonoglou, Aja Huang, Arthur Guez, Thomas Hubert, Lucas Baker, Matthew Lai, Adrian Bolton, et al. 2017 · 2017
Earlier work this paper cites.
Decoupling strategy and generation in negotiation dialogues
He He, Derek Chen, Anusha Balakrishnan, and Percy Liang. 2018 · 2018
Earlier work this paper cites.
Finding friend and foe in multi-agent games
Jack Serrino, Max Kleiman-Weiner, David C Parkes, and Josh Tenenbaum. 2019 · 2019
Earlier work this paper cites.
Human-level play in the game of diplomacy by combining language models with strategic reasoning
Meta Fundamental AI Research Diplomacy Team (FAIR)†, Anton Bakhtin, Noam Brown, Emily Dinan, Gabriele Farina, Colin Flaherty, Daniel Fried, Andrew Goff, Jonathan Gray, Hengyuan Hu, et al. 2022 · 2022
Earlier work this paper cites.
A generalist agent
Scott Reed, Konrad Zolna, Emilio Parisotto, Sergio Gómez Colmenarejo, Alexander Novikov, Gabriel Barth-maron, Mai Giménez, Yury Sulsky, Jackie Kay, Jost Tobias Springenberg, et al. 2022 · 2022
Earlier work this paper cites.
Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al. 2022 · 2022
Earlier work this paper cites.
Llm-based agent society investigation: Collaboration and confrontation in avalon gameplay
Yihuai Lan, Zhiqiang Hu, Lei Wang, Yang Wang, Deheng Ye, Peilin Zhao, Ee-Peng Lim, Hui Xiong, and Hao Wang. 2023 · 2023
Earlier work this paper cites.
Avalonbench: Evaluating llms playing the game of avalon
Jonathan Light, Min Cai, Sheng Shen, and Ziniu Hu. 2023 · 2023
Earlier work this paper cites.
Generative agents: Interactive simulacra of human behavior
Joon Sung Park, Joseph O’Brien, Carrie Jun Cai, Meredith Ringel Morris, Percy Liang, and Michael S Bernstein. 2023 · 2023
Earlier work this paper cites.
Managing the risks of artificial general intelligence: A human factors and ergonomics perspective
Paul M Salmon, Chris Baber, Catherine Burns, Tony Carden, Nancy Cooke, Missy Cummings, Peter Hancock, Scott McLean, Gemma JM Read, and Neville A Stanton. 2023 · 2023
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Dialogue games for benchmarking language understanding: Motivation, taxonomy, strategy
David Schlangen. 2023 · 2023
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Character-llm: A trainable agent for role-playing
Yunfan Shao, Linyang Li, Junqi Dai, and Xipeng Qiu. 2023 · 2023
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Cognitive architectures for language agents
Theodore Sumers, Shunyu Yao, Karthik Narasimhan, and Thomas Griffiths. 2023 · 2023
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Avalon’s game of thoughts: Battle against deception through recursive contemplation
Shenzhi Wang, Chang Liu, Zilong Zheng, Siyuan Qi, Shuo Chen, Qisen Yang, Andrew Zhao, Chaofei Wang, Shiji Song, and Gao Huang. 2023 · 2023
Step-dpo: Step-wise preference optimization for long-chain reasoning of llms
Xin Lai, Zhuotao Tian, Yukang Chen, Senqiao Yang, Xiangru Peng, and Jiaya Jia. 2024 · 2024
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Simpo: Simple preference optimization with a reference-free reward
Yu Meng, Mengzhou Xia, and Danqi Chen. 2024 · 2024
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Agentsense: Benchmarking social intelligence of language agents through interactive scenarios
Xinyi Mou, Jingcong Liang, Jiayu Lin, Xinnong Zhang, Xiawei Liu, Shiyue Yang, Rong Ye, Lei Chen, Haoyu Kuang, Xuanjing Huang, et al. 2024 · 2024
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Smaug: Fixing failure modes of preference optimisation with dpo-positive
Arka Pal, Deep Karkhanis, Samuel Dooley, Manley Roberts, Siddartha Naidu, and Colin White. 2024 · 2024
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Cited alongside, same era.
Dekun Wu, Haochen Shi, Zhiyuan Sun, and Bang Liu. 2023 · 2023
Cited alongside, same era.
Exploring large language models for communication games: An empirical study on werewolf
Yuzhuang Xu, Shuo Wang, Peng Li, Fuwen Luo, Xiaolong Wang, Weidong Liu, and Yang Liu. 2023 · 2023
Cited alongside, same era.
Agenttuning: Enabling generalized agent abilities for llms
Aohan Zeng, Mingdao Liu, Rui Lu, Bowen Wang, Xiao Liu, Yuxiao Dong, and Jie Tang. 2023 · 2023
Cited alongside, same era.
Werewolf arena: A case study in llm evaluation via social deduction
Suma Bailis, Jane Friedhoff, and Feiyang Chen. 2024 · 2024
Cited alongside, same era.
Language evolution for evading social media regulation via llm-based multi-agent simulation
Jinyu Cai, Jialong Li, Mingyue Zhang, Munan Li, Chen-Shu Wang, and Kenji Tei. 2024 · 2024
Cited alongside, same era.
Self-playing adversarial language game enhances llm reasoning
Pengyu Cheng, Tianhao Hu, Han Xu, Zhisong Zhang, Yong Dai, Lei Han, and Nan Du. 2024 · 2024
Cited alongside, same era.
Amongagents: Evaluating large language models in the interactive text-based social deduction game
Yizhou Chi, Lingjun Mao, and Zineng Tang. 2024 · 2024
Cited alongside, same era.
Pranav Putta, Edmund Mills, Naman Garg, Sumeet Motwani, Chelsea Finn, Divyansh Garg, and Rafael Rafailov. 2024 · 2024
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Direct preference optimization: Your language model is secretly a reward model
Rafael Rafailov, Archit Sharma, Eric Mitchell, Christopher D Manning, Stefano Ermon, and Chelsea Finn. 2024 · 2024
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An implementation of werewolf agent that does not truly trust llms
Takehiro Sato, Shintaro Ozaki, and Daisaku Yokoyama. 2024 · 2024
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Boundless socratic learning with language games
Tom Schaul. 2024 · 2024
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Trial and error: Exploration-based trajectory optimization for llm agents
Yifan Song, Da Yin, Xiang Yue, Jie Huang, Sujian Li, and Bill Yuchen Lin. 2024 · 2024
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Generative emergent communication: Large language model is a collective world model
Tadahiro Taniguchi, Ryo Ueda, Tomoaki Nakamura, Masahiro Suzuki, and Akira Taniguchi. 2024 · 2024
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Measuring bullshit in the language games played by chatgpt
Alessandro Trevisan, Harry Giddens, Sarah Dillon, and Alan F Blackwell. 2024 · 2024
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Enhance reasoning for large language models in the game werewolf
Shuang Wu, Liwen Zhu, Tao Yang, Shiwei Xu, Qiang Fu, Yang Wei, and Haobo Fu. 2024 · 2024
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Agentgym: Evolving large language model-based agents across diverse environments
Zhiheng Xi, Yiwen Ding, Wenxiang Chen, Boyang Hong, Honglin Guo, Junzhe Wang, Dingwen Yang, Chenyang Liao, Xin Guo, Wei He, et al. 2024 · 2024
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Watch every step! llm agent learning via iterative step-level process refinement
Weimin Xiong, Yifan Song, Xiutian Zhao, Wenhao Wu, Xun Wang, Ke Wang, Cheng Li, Wei Peng, and Sujian Li. 2024 · 2024
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Language agents with reinforcement learning for strategic play in the werewolf game
Zelai Xu, Chao Yu, Fei Fang, Yu Wang, and Yi Wu. 2024 · 2024
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Finding deceivers in social context with large language models and how to find them: the case of the mafia game
Byunghwa Yoo and Kyung-Joong Kim. 2024 · 2024
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Agent-pro: Learning to evolve via policy-level reflection and optimization
Wenqi Zhang, Ke Tang, Hai Wu, Mengna Wang, Yongliang Shen, Guiyang Hou, Zeqi Tan, Peng Li, Yueting Zhuang, and Weiming Lu. 2024 · 2024
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Expel: Llm agents are experiential learners
Andrew Zhao, Daniel Huang, Quentin Xu, Matthieu Lin, Yong-Jin Liu, and Gao Huang. 2024 · 2024
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