Fetching the paper…
Reading the bibliography…
We present PORTAL, a novel framework for developing artificial intelligence agents capable of playing thousands of 3D video games through language-guided policy generation.
Programming a computer for playing chess
Claude E. Shannon · 1950
Earlier work this paper cites.
Between MDPs and semi-MDPs, a framework for temporal abstraction in reinforcement learning
Richard S Sutton, Doina Precup, and Satinder Singh · 1999
Earlier work this paper cites.
Human-level control through deep reinforcement learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A. Rusu, Joel Veness, Marc G. Bellemare, Alex Graves, Martin Riedmiller, Andreas K. Fidjeland, Georg Ostrovski, Stig Petersen, Charles Beattie, Amir Sadik, Ioannis Antonoglou, Helen King, Dharshan Kumaran, Daan Wierstra, Shane Legg, and Demis Hassabis · 2015
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, Sander Dieleman, Dominik Grewe, John Nham, Nal Kalchbrenner, Ilya Sutskever, Timothy Lillicrap, Madeleine Leach, Koray Kavukcuoglu, Thore Graepel, and Demis Hassabis · 2016
Earlier work this paper cites.
Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 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, Yutian Chen, Timothy Lillicrap, Fan Hui, Laurent Sifre, George van den Driessche, Thore Graepel, and Demis Hassabis · 2017
Earlier work this paper cites.
Behavior Trees in Robotics and AI: An Introduction
Michele Colledanchise and Petter Ögren · 2018
Earlier work this paper cites.
IMPALA: Scalable distributed deep-RL with importance weighted actor-learner architectures
Lasse Espeholt, Hubert Soyer, Rémi Munos, Karen Simonyan, Volodymyr Mnih, Tom Ward, Yotam Doron, Vlad Firoiu, Tim Harley, Iain Dunning, Shane Legg, and Koray Kavukcuoglu · 2018
Earlier work this paper cites.
A general reinforcement learning algorithm that masters Chess, Shogi, and Go through self-play
David Silver, Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Matthew Lai, Arthur Guez, Marc Lanctot, Laurent Sifre, Dharshan Kumaran, Thore Graepel, Timothy Lillicrap, Karen Simonyan, and Demis Hassabis · 2018
Earlier work this paper cites.
Reinforcement Learning: An Introduction
Richard S Sutton and Andrew G Barto · 2018
Earlier work this paper cites.
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, Chelsea Hunn, Imanol Luengo, Jack Rae, Rachel H, Bob McGrew, Tyna Eloundou Nekoul, Matthias Plappert, Dario Amodei, and Wojciech Zaremba · 2019
Cited alongside, same era.
Grandmaster level in StarCraft II using multi-agent reinforcement learning
Oriol Vinyals, Igor Babuschkin, Wojciech M. Czarnecki, Michaël Mathieu, Andrew Dudzik, Junyoung Chung, David H. Choi, Richard Powell, Timo Ewalds, Tom Eccles, Norman Casares, Thomas Budden, Simon Osindero, Aliaksei Veliantsev, Johannes Agapiou, James Devlin, Yuval Tassa, Brendan Tracey, Demis Hassabis, and Koray Kavukcuoglu · 2019
Cited alongside, same era.
Mastering complex control in MOBA games with deep reinforcement learning
Deheng Ye, Zhao Liu, Mingfei Sun, Bei Shi, Peilin Zhao, Hao Wu, Hongsheng Yu, Shaojie Yang, Xipeng Wu, Qingwei Guo, Qiaobo Chen, Yinyuting Yin, Hao Zhang, Tengfei Shi, Liang Wang, Qiang Fu, Wei Yang, and Lanxiao Huang · 2020
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 Chi, Quoc Le, and Denny Zhou · 2022
Cited alongside, same era.
ReAct: Synergizing reasoning and acting in language models
Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, and Yuan Cao · 2023
Later among the works it cites.
Large language models and games: A survey and roadmap
Roberto Gallotta, Graham Todd, Marvin Zammit, Sam Earle, Antonios Liapis, Julian Togelius, and Georgios N Yannakakis · 2024
Later among the works it cites.
Large language models play StarCraft II: Benchmarks and a chain of summarization approach
Weiyu Ma, Qirui Mi, Yongcheng Zeng, Xue Yan, Runji Lin, Yuqiao Wu, Jun Wang, and Haifeng Zhang · 2024
Later among the works it cites.
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Gemini Team, Petko Georgiev, Ving Ian Lei, Ryan Burnell, Libin Bai, Anmol Gulati, Garrett Tanzer, Damien Vincent, Zhufeng Pan, Shibo Wang, et al · 2024
Later among the works it cites.
OpenHands: An Open Platform for AI Software Developers as Generalist Agents, 2024
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
OpenAI, Josh Achiam, Sasha Adler, Sandhini Agarwal, Sandeep Ahmad, Ilge Akkaya, Alty Aleman, David Almeida, Elie Altman, Alekh Alvarez, Haiming Anderson, Mira Anderson, Jyoti Aneja, Anthony Anton, Amanda Askell, Haidar Aslam, Alex Azer, Karsen Bach, Yuntao Bai, Mark Balwit, Kendra Banks, Kaylee Batmanghelich, Daniel Baxter, Pierre Beres, Stella Biderman, Nicholas Burnell, Alessandro Achille, et al · 2023
Cited alongside, same era.
ToolLLM: Facilitating large language models to master 16000+ real-world APIs
Yujia Qin, Shengding Liang, Houqiang Ye, Ge Liu, Yi Zhang, Weizhu Han, Xin Jin, Lifan Yang, Nianwen Xue, Jiawei Han, and Jie Tang · 2023
Cited alongside, same era.
Toolformer: Language models can teach themselves to use tools
Timo Schick, Jane Dwivedi-Yu, Roberto Dessì, Roberta Raileanu, Maria Lomeli, Luke Zettlemoyer, Nicola Cancedda, and Thomas Scialom · 2023
Cited alongside, same era.
Reflexion: Language agents with verbal reinforcement learning, 2023
Noah Shinn, Federico Cassano, Edward Berman, Ashwin Gopinath, Karthik Narasimhan, and Shunyu Yao · 2023
Cited alongside, same era.
Can large language models play text games well? Current state-of-the-art and open questions
Chen Feng Tsai, Xiaochen Zhou, Sierra S Liu, Jing Li, Mo Yu, and Hongyuan Mei · 2023
Cited alongside, same era.
VOYAGER: An open-ended embodied agent with large language models
Guanzhi Wang, Yuqi Xie, Yunfan Jiang, Ajay Mandlekar, Chaowei Xiao, Yuke Zhu, Linxi Fan, and Anima Anandkumar · 2023
Cited alongside, same era.
Qwen2.5: An innovative, generalist, and open large language model family
Qwen Team
Cited in the paper.
Qwen2.5-Coder: An enhanced large language model for code understanding and generation
Qwen Team
Cited in the paper.
Xingyao Wang, Boxuan Li, Yufan Song, Frank F. Xu, Xiangru Tang, Mingchen Zhuge, Jiayi Pan, Yueqi Song, Bowen Li, Jaskirat Singh, Hoang H. Tran, Fuqiang Li, Ren Ma, Mingzhang Zheng, Bill Qian, Yanjun Shao, Niklas Muennighoff, Yizhe Zhang, Binyuan Hui, Junyang Lin, Robert Brennan, Hao Peng, Heng Ji, and Graham Neubig · 2024
Later among the works it cites.
Visible extended thinking in large language models
Anthropic · 2025
Closest in time.
DeepSeek-R1: Incentivizing reasoning capability in LLMs via reinforcement learning
DeepSeek-AI, Daya Guo, Dejian Yang, Haowei Zhang, Junxiao Song, Ruoyu Zhang, Runxin Xu, Qihao Zhu, Shirong Ma, Peiyi Wang, Xiao Bi, Xiaokang Zhang, and … (add other authors as needed or use et al.) · 2025
Closest in time.
Gemini Robotics: Bringing AI into the physical world
Gemini Robotics Team, Google DeepMind · 2025
Closest in time.
Mineflayer: A high-level JavaScript API for creating Minecraft bots
PrismarineJS · 2025
Closest in time.
Towards System 2 reasoning in LLMs: Learning how to think with meta Chain-of-Thought
Violet Xiang, Charlie Snell, Kanishk Gandhi, Alon Albalak, Anikait Singh, Chase Blagden, Duy Phung, Rafael Rafailov, Nathan Lile, Dakota Mahan, et al · 2025
Closest in time.