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Algorithmic reasoning is a fundamental cognitive ability that plays a pivotal role in problem-solving and decision-making processes.
OpenSpiel: A framework for reinforcement learning in games
Marc Lanctot, Edward Lockhart, Jean-Baptiste Lespiau, Vinicius Zambaldi, Satyaki Upadhyay, Julien Pérolat, Sriram Srinivasan, Finbarr Timbers, Karl Tuyls, Shayegan Omidshafiei, Daniel Hennes, Dustin Morrill, Paul Muller, Timo Ewalds, Ryan Faulkner, János Kramár, Bart De Vylder, Brennan Saeta, James Bradbury, David Ding, Sebastian Borgeaud, Matthew Lai, Julian Schrittwieser, Thomas Anthony, Edward Hughes, Ivo Danihelka, and Jonah Ryan-Davis · 1908
Earlier work this paper cites.
A reinforcement learning algorithm applied to simplified two-player texas hold’em poker
Fredrik A Dahl · 2001
Earlier work this paper cites.
Reinforcement learning in board games
Imran Ghory · 2004
Earlier work this paper cites.
Mujoco: A physics engine for model-based control
Emanuel Todorov, Tom Erez, and Yuval Tassa · 2012
Earlier work this paper cites.
Reinforcement learning in games
István Szita · 2012
Earlier work this paper cites.
Playing Atari with Deep Reinforcement Learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Alex Graves, Ioannis Antonoglou, Daan Wierstra, and Martin A. Riedmiller · 2013
Earlier work this paper cites.
The arcade learning environment: An evaluation platform for general agents
Marc G Bellemare, Yavar Naddaf, Joel Veness, and Michael Bowling · 2013
Earlier work this paper cites.
Giraffe: Using deep reinforcement learning to play chess
Matthew Lai · 2015
Earlier work this paper cites.
Trust region policy optimization
John Schulman, Sergey Levine, Pieter Abbeel, Michael Jordan, and Philipp Moritz · 2015
Earlier work this paper cites.
Logic tensor networks: Deep learning and logical reasoning from data and knowledge
Luciano Serafini and Artur d’Avila Garcez · 2016
Earlier work this paper cites.
Greg Brockman, Vicki Cheung, Ludwig Pettersson, Jonas Schneider, John Schulman, Jie Tang, and Wojciech Zaremba · 2016
Earlier work this paper cites.
Benchmarking deep reinforcement learning for continuous control
Yan Duan, Xi Chen, Rein Houthooft, John Schulman, and Pieter Abbeel · 2016
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.
Deep reinforcement learning from self-play in imperfect-information games
Johannes Heinrich and David Silver · 2016
Earlier work this paper cites.
Asynchronous methods for deep reinforcement learning
Volodymyr Mnih, Adrià Puigdomènech Badia, Mehdi Mirza, Alex Graves, Timothy P. Lillicrap, Tim Harley, David Silver, and Koray Kavukcuoglu · 2016
Earlier work this paper cites.
# exploration: A study of count-based exploration for deep reinforcement learning
Haoran Tang, Rein Houthooft, Davis Foote, Adam Stooke, OpenAI Xi Chen, Yan Duan, John Schulman, Filip DeTurck, and Pieter Abbeel · 2017
Earlier work this paper cites.
Mastering chess and shogi by self-play with a general reinforcement learning algorithm
David Silver, Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Matthew Lai, Arthur Guez, Marc Lanctot, Laurent Sifre, Dharshan Kumaran, Thore Graepel, et al · 2017
Earlier work this paper cites.
Proximal policy optimization algorithms, 2017
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
Earlier work this paper cites.
Distributional reinforcement learning with quantile regression
Will Dabney, Mark Rowland, Marc G. Bellemare, and Rémi Munos · 2017
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, et al · 2018
Earlier work this paper cites.
Scalable deep reinforcement learning for vision-based robotic manipulation
Dmitry Kalashnikov, Alex Irpan, Peter Pastor, Julian Ibarz, Alexander Herzog, Eric Jang, Deirdre Quillen, Ethan Holly, Mrinal Kalakrishnan, Vincent Vanhoucke, et al · 2018
Earlier work this paper cites.
Yuval Tassa, Yotam Doron, Alistair Muldal, Tom Erez, Yazhe Li, Diego de Las Casas, David Budden, Abbas Abdolmaleki, Josh Merel, Andrew Lefrancq, et al · 2018
Earlier work this paper cites.
Textworld: A learning environment for text-based games
Marc-Alexandre Côté, Ákos Kádár, Xingdi Yuan, Ben Kybartas, Tavian Barnes, Emery Fine, James Moore, Ruo Yu Tao, Matthew Hausknecht, Layla El Asri, Mahmoud Adada, Wendy Tay, and Adam Trischler · 2018
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Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor
Tuomas Haarnoja, Aurick Zhou, Pieter Abbeel, and Sergey Levine · 2018
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Addressing function approximation error in actor-critic methods
Scott Fujimoto, Herke Hoof, and David Meger · 2018
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Bridging machine learning and logical reasoning by abductive learning
Wang-Zhou Dai, Qiuling Xu, Yang Yu, and Zhi-Hua Zhou · 2019
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Neural logic reinforcement learning
Zhengyao Jiang and Shan Luo · 2019
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Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, Abu Awal Md Shoeb, Abubakar Abid, Adam Fisch, Adam R Brown, Adam Santoro, Aditya Gupta, Adrià Garriga-Alonso, et al · 2022
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Outracing champion gran turismo drivers with deep reinforcement learning
Peter R Wurman, Samuel Barrett, Kenta Kawamoto, James MacGlashan, Kaushik Subramanian, Thomas J Walsh, Roberto Capobianco, Alisa Devlic, Franziska Eckert, Florian Fuchs, et al · 2022
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Learning to walk in minutes using massively parallel deep reinforcement learning
Nikita Rudin, David Hoeller, Philipp Reist, and Marco Hutter · 2022
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Deep reinforcement learning-based path control and optimization for unmanned ships
Di Wu, Yin Lei, Maoen He, Chunjiong Zhang, and Li Ji · 2022
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Safe learning in robotics: From learning-based control to safe reinforcement learning
Lukas Brunke, Melissa Greeff, Adam W Hall, Zhaocong Yuan, Siqi Zhou, Jacopo Panerati, and Angela P Schoellig · 2022
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Ishita Dasgupta, Jane Wang, Silvia Chiappa, Jovana Mitrovic, Pedro Ortega, David Raposo, Edward Hughes, Peter Battaglia, Matthew Botvinick, and Zeb Kurth-Nelson · 2019
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Deep reinforcement learning in strategic board game environments
Konstantia Xenou, Georgios Chalkiadakis, and Stergos Afantenos · 2019
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Muzero general: Open reimplementation of muzero
Aurèle Hainaut Werner Duvaud · 2019
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Strong generalization and efficiency in neural programs
Yujia Li, Felix Gimeno, Pushmeet Kohli, and Oriol Vinyals · 2020
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Agent57: Outperforming the atari human benchmark
Adrià Puigdomènech Badia, Bilal Piot, Steven Kapturowski, Pablo Sprechmann, Alex Vitvitskyi, Zhaohan Daniel Guo, and Charles Blundell · 2020
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Reinforcement learning for building controls: The opportunities and challenges
Zhe Wang and Tianzhen Hong · 2020
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Mastering atari, go, chess and shogi by planning with a learned model
Julian Schrittwieser, Ioannis Antonoglou, Thomas Hubert, Karen Simonyan, Laurent Sifre, Simon Schmitt, Arthur Guez, Edward Lockhart, Demis Hassabis, Thore Graepel, et al · 2020
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Discovering faster matrix multiplication algorithms with reinforcement learning
Alhussein Fawzi, Matej Balog, Aja Huang, Thomas Hubert, Bernardino Romera-Paredes, Mohammadamin Barekatain, Alexander Novikov, Francisco J R Ruiz, Julian Schrittwieser, Grzegorz Swirszcz, et al · 2022
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Rethinking reinforcement learning based logic synthesis
Chao Wang, Chen Chen, Dong Li, and Bin Wang · 2022
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Intelligent problem-solving as integrated hierarchical reinforcement learning
Manfred Eppe, Christian Gumbsch, Matthias Kerzel, Phuong DH Nguyen, Martin V Butz, and Stefan Wermter · 2022
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Continuous neural algorithmic planners
Yu He, Petar Veličković, Pietro Liò, and Andreea Deac · 2022
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Alphaholdem: High-performance artificial intelligence for heads-up no-limit poker via end-to-end reinforcement learning
Enmin Zhao, Renye Yan, Jinqiu Li, Kai Li, and Junliang Xing · 2022
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Mastering the game of stratego with model-free multiagent reinforcement learning
Julien Perolat, Bart De Vylder, Daniel Hennes, Eugene Tarassov, Florian Strub, Vincent de Boer, Paul Muller, Jerome T Connor, Neil Burch, Thomas Anthony, et al · 2022
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Introduction to Algorithms
Thomas H. Cormen, Charles Eric Leiserson, Ronald L. Rivest, and Clifford Stein · 2022
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Scalar reward is not enough: A response to silver, singh, precup and sutton (2021)
Peter Vamplew, Benjamin J Smith, Johan Källström, Gabriel Ramos, Roxana Rădulescu, Diederik M Roijers, Conor F Hayes, Fredrik Heintz, Patrick Mannion, Pieter JK Libin, et al · 2022
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The 37 implementation details of proximal policy optimization
Shengyi Huang, Rousslan Fernand Julien Dossa, Antonin Raffin, Anssi Kanervisto, and Weixun Wang · 2022
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Machine learning and logical reasoning: The new frontier (dagstuhl seminar 22291)
Sébastien Bardin, Somesh Jha, and Vijay Ganesh · 2023
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Residual skill policies: Learning an adaptable skill-based action space for reinforcement learning for robotics
Krishan Rana, Ming Xu, Brendan Tidd, Michael Milford, and Niko Sünderhauf · 2023
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Faster sorting algorithms discovered using deep reinforcement learning
Daniel J Mankowitz, Andrea Michi, Anton Zhernov, Marco Gelmi, Marco Selvi, Cosmin Paduraru, Edouard Leurent, Shariq Iqbal, Jean-Baptiste Lespiau, Alex Ahern, et al · 2023
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Simon tatham’s portable puzzle collection, 2004a
Simon Tatham · 2023
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Gymnasium website, 2022
Farama Foundation · 2023
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Pygame github repository, 2000
Pygame Community · 2023
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Developer documentation for simon tatham’s puzzle collection, 2004b
Simon Tatham · 2023
Later among the works it cites.