Methods › Reinforcement Learning › Board Game Models › AlphaZero › Papers, page 2

AlphaZero

Papers archive 2025-07-28

archive papers tagged: 114 · with a code link: 60 · where Syntology ran a sample: 17 (16 with a run with no instrument failure, 1 where every run was a failure of Syntology's instrument) Syntology

Show: all tagged papersonly where code ran (17 of 114 tagged: 16 with a run with no instrument failure, 1 where every run was a failure of Syntology's instrument)

Page 2 of 2: papers 101 to 114 of 114, newest first by the archive's date (ties by slug), in archive order.

Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code, as “N ran (of which C constructed an object rather than computing a result; K with no instrument failure: H honoured, V violated, P with no contract checked; I where Syntology's instrument failed) · U unverified”; the instrument figure counts failures of Syntology's instrument, not of the code. It is per sample and not a correctness claim. When the archive marks a repository official for the paper, the line starts with that repository's state (the archive's flag, not a verdict on who wrote the code; “community repositories only” when every sample that ran came from a community repository, “official: no sample here; runs from other or unrecorded repositories” when some came from a repository the paper names or has in its text, or from none recorded); hover it for the repositories the samples that ran came from.

• Performing Deep Recurrent Double Q-Learning for Atari Games
  16 Aug 2019 · 2 repositories · arXiv:1908.06040
• Multiple Policy Value Monte Carlo Tree Search
  31 May 2019 · 2 repositories · arXiv:1905.13521
• Learning Compositional Neural Programs with Recursive Tree Search and Planning
  30 May 2019 · 1 repository · arXiv:1905.12941
• Deep Policies for Width-Based Planning in Pixel Domains
  12 Apr 2019 · 1 repository · arXiv:1904.07091
• Improved Reinforcement Learning with Curriculum
  29 Mar 2019 · 0 repositories · arXiv:1903.12328
• Hyper-Parameter Sweep on AlphaZero General
  19 Mar 2019 · 1 repository · arXiv:1903.08129
• α-Rank: Multi-Agent Evaluation by Evolution
  4 Mar 2019 · 1 repository · arXiv:1903.01373
• Accelerating Self-Play Learning in Go
  27 Feb 2019 · 6 repositories · arXiv:1902.10565
• ELF OpenGo: An Analysis and Open Reimplementation of AlphaZero
  12 Feb 2019 · 1 repository · arXiv:1902.04522
• The Entropy of Artificial Intelligence and a Case Study of AlphaZero from Shannon's Perspective
  14 Dec 2018 · 0 repositories · arXiv:1812.05794
• Assessing the Potential of Classical Q-learning in General Game Playing
  14 Oct 2018 · 1 repository · arXiv:1810.06078
• ExIt-OOS: Towards Learning from Planning in Imperfect Information Games
  30 Aug 2018 · 1 repository · arXiv:1808.10120
• Ranked Reward: Enabling Self-Play Reinforcement Learning for Combinatorial Optimization
  4 Jul 2018 · 2 repositories · arXiv:1807.01672
• Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
  5 Dec 2017 · 62 repositories · arXiv:1712.01815
  Syntology 13 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 3 honoured, 1 violated, 0 with no contract checked; 9 where Syntology's instrument failed) · 4 unverified (of 17 harvested samples) · 9 pointer-only (licence)