Bibliography:

  1. doc tag

  2. ‘AI chess’ tag

  3. ‘DeepMind’ tag

  4. ‘data pruning’ tag

  5. ‘active learning’ tag

  6. ‘RL exploration’ tag

  7. ‘brain imitation learning’ tag

  8. ‘imitation learning’ tag

  9. Diplomacy AI’ tag

  10. Hanabi AI’ tag

  11. ‘hidden-information game’ tag

  12. ‘poker AI’ tag

  13. ‘continual learning’ tag

  14. ‘meta-learning’ tag

  15. ‘AlphaStar’ tag

  16. ‘model-free RL’ tag

  17. ‘OA5’ tag

  18. ‘AlphaGo’ tag

  19. ‘Decision Transformer’ tag

  20. ‘model-based RL’ tag

  21. ‘MuZero’ tag

  22. ‘MARL’ tag

  23. Nethack AI’ tag

  24. ‘offline RL’ tag

  25. ‘OA’ tag

  26. ‘preference learning’ tag

  27. ‘AI mode collapse’ tag

  28. ‘robotics’ tag

  29. /doc/reinforcement-learning/safe/clippy

  30. ‘AI safety’ tag

  31. ‘RL scaling’ tag

  32. ‘video analysis’ tag

  33. ‘cellular automata’ tag

  34. Foundations for Transfer in Reinforcement Learning: A Taxonomy of Knowledge Modalities

  35. PiRank: Learning To Rank via Differentiable Sorting

  36. Rank-Smoothed Pairwise Learning In Perceptual Quality Assessment

  37. Deep Reinforcement Learning for Closed-Loop Blood Glucose Control

  38. Multi-Task Learning with Deep Neural Networks: A Survey

  39. Algorithms with Predictions

  40. Systems that defy detailed understanding § Deep reinforcement Learning

  41. Monte Carlo Gradient Estimation in Machine Learning

  42. Evolving super stimuli for real neurons using deep generative networks

  43. An Overview of Multi-Task Learning in Deep Neural Networks

  44. On the Computability of Solomonoff Induction and AIXI

  45. Do Artificial Reinforcement-Learning Agents Matter Morally?

  46. Advanced Forecasting Methods for Global Crisis Warning and Models of Intelligence

  47. Sutton & Barto Book: Reinforcement Learning: An Introduction

  48. d17be0ceaaf87dec3530beee7d43105623574f4f.html

  49. Learning to Simulate Dynamic Environments With GameGAN (CVPR 2020)

  50. Adversarial Machine Learning

  51. a1d36a41223f2f4cf6b348be17328dc1eb789447.html

  52. Deep Reinforcement Learning Doesn't Work Yet

  53. Reddit: Reinforcement Learning subreddit

  54. design#future-tag-features

    [Transclude the forward-link's context]

  55. 2020-real-googlebrain-automlzero-populationperformanceevolution.mp4

  56. 2018-07-26-synced-googleaichiefjeffdeansmlsystemarchitectureblueprint.html

  57. 2018-metz-table1-metalearningparadigms.png

  58. 2017-12-24-gwern-meme-nnlayers-alphagozero.jpg

  59. 2016-hein.pdf

  60. 2013-vien.pdf

  61. 2004-cook-twoneuronbicycle.avi

  62. 2004-cook-twoneuronbicycle.avi-poster.jpg

  63. 1993-lin.pdf

  64. 1990-barto.pdf

  65. 1989-sutton.pdf

  66. 1960-howard-dynamicprogrammingmarkovprocesses.pdf

  67. http://amid.fish/reproducing-deep-rl

  68. 629ac9c4c117f9413996372f0a42896f3230b5bb.html

  69. https://ai.facebook.com/blog/yann-lecun-advances-in-ai-research

  70. https://rll.berkeley.edu/deeprlcourse/docs/nuts-and-bolts.pdf

  71. 38653211f188d824648f5792cd852e12033b18dd.pdf

  72. https://www.quantamagazine.org/in-new-math-proofs-artificial-intelligence-plays-to-win-20220307/

  73. Systems that defy detailed understanding § Deep reinforcement Learning

  74. https%253A%252F%252Fblog.nelhage.com%252Fpost%252Fsystems-that-defy-understanding%252F.html

  75. Wikipedia Bibliography:

    1. Learning to Rank