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Unlock Your Potential: Top 10 Reasons to Learn Python Python is one of the most popular programming languages in the world. As technology advances and more companies use Python … Read More C# course from scratch for beginners If you have only a general idea of what programming is and have never been professionally engaged in it, we recommend that you start learning from the very basics. Read More
Simple Beginner's guide to Reinforcement Learning & its implementation
One of the most fundamental questions in the field of reinforcement learning for scientists across the globe has been – “How to learn a new skill?â€. The desire to understand the answer is obvious – if we can understand this, we can enable human species to do things we might not have thought before. Alternately, we can train machines using reinforcement learning to do more “human†tasks and create
TensorFlowã§TicTacToeã«æŒ‘戦 - Qiita
#æ¦‚è¦ TnsorFlowã§TicTacToeã‚’ã‚„ã‚‹ãŸã‚ã«ã€OpenAiGymã®TicTacToe環境作ã£ã¦è¦‹ãŸã€‚ 手ã§ç¢ºèªç”¨ã®ã‚µãƒ³ãƒ—ルコードã€è¼‰ã›ã‚‹ã€‚ 誰ã‹ãŒã€TensorFlowã§è² ã‹ã›ã¦ãれる事を望む。 #写真 #環境 windows 7 sp1 64bit anaconda3 tensorflow 1.0 OpenAi Gym 0.5 #TicTacToe環境ã®æ¦‚è¦ ##observe: 3*3ã®ç›¤é¢ã‚’0ã‹ã‚‰9ã¾ã§ã®é…列ã«ã—ã¦è¿”ã™ 0 1 2 3 4 5 6 7 8 0 ãªã— 1　白 -1　黒 ##reward: å‹ã£ãŸã‚‰1 何も0 è² ã‘ãŸã‚‰-1 ##gameOver: 盤ãŒåŸ‹ã¾ã£ãŸã‹ã€3ã¤ä¸¦ã‚“ã ã‹ã€‚ ##action: 0ã‹ã‚‰8ã§æŒ‡å®šã€‚ -1ãªã‚‰ç›¸æ‰‹ã€‚ #確èªç”¨ã®ã‚µãƒ³ãƒ—ルコード from __future__ import print_function import math i
keras-rl ã® example コードを実行ã™ã‚‹ã ã‘ - クッã‚ーã®æ—¥è¨˜
Keras を勉強ã—ã¾ã™ã€‚ keras-rl ã§ã‚ªãƒªã‚¸ãƒŠãƒ«ã®å¼·åŒ–å¦ç¿’タスク・オリジナルã®DQNモデルをå¦ç¿’ã—ãŸã¨ã„ã†è¨˜äº‹ãŒæœ¬æ—¥ Qiita ã«æŠ•ç¨¿ã•ã‚Œã¦ã„ã¾ã—ãŸãŒï¼ˆå‚考記事）ã€ã¾ãš keras-rl 㨠gym ãŒã‚ã‹ã‚‰ãªã„ã®ã§ example コードを実行ã™ã‚‹ã“ã¨ã«ã—ã¾ã™ã€‚ å‚考記事 ã‚„ã‚‹ã“ã¨ æ‰‹é † 感想 å‚考記事 以下ã®è¨˜äº‹ã‚’å‚考ã«ã•ã›ã¦ã„ãŸã ãã¾ã—ãŸãŒã€ã‚„ã£ãŸã“ã¨ã¯è¨˜äº‹å†…容ã®ãƒˆãƒ¬ãƒ¼ã‚¹ã‚ˆã‚Šã¯ã‚‹ã‹ä½Žã¿ã§ã™ã€‚ qiita.com ã‚„ã‚‹ã“㨠強化å¦ç¿’ã§ä¼çµ±çš„ãªãƒãƒ¼ãƒ«ãƒãƒ©ãƒ³ã‚·ãƒ³ã‚°ã‚¿ã‚¹ã‚¯ã‚’エージェントã«å¦ç¿’ã•ã›ã¾ã™ã€‚ å°å¦ç”Ÿã®ã¨ã掃除ã®æ™‚é–“ã«ã€æ‰‹ã®ã²ã‚‰ã«ç®’ã‚’ã®ã›ã¦å€’ã‚Œãªã„よã†ã«ãƒãƒ©ãƒ³ã‚¹ã‚’å–ã‚‹ã®ã‚’よãã‚„ã£ãŸã¨æ€ã„ã¾ã™ã€‚ 今回ã®ã‚¿ã‚¹ã‚¯ã®ãƒãƒ¼ãƒ«ã®å‹•ã範囲ã¯2次元平é¢å†…ã«åˆ¶ç´„ã•ã‚Œã¦ã„ã¾ã™ã€‚å°è»Šã‚‚直線上を動ãã¾ã™ã€‚ gym ã§ã®ã‚¿ã‚¹ã‚¯è¨å®šã¯ä»¥ä¸‹ã®ãƒšãƒ¼ã‚¸å‚照。 OpenAI Gym CartPole-v0
ライントレーサーã®ç’°å¢ƒã‚’OpenAI I/Fçš„ã«ã—㟠- Qiita
ライントレーサーをDeep Q Learningã§æ•™è‚²ã™ã‚‹ - Chainer - Qiitaã§å–り扱ã£ãŸç’°å¢ƒã‚’OpenAI gymライクã«æ‰±ãˆã‚‹ã‚ˆã†ã«ç’°å¢ƒã¨AIを分離・整備ã—ã¾ã—ãŸã€‚分離ã—ãŸã¨ã„ã£ã¦ã‚‚ã€renderã®ã¨ã“ã‚を当åˆwxPythonã¨æ画・ãƒã‚¸ãƒƒã‚¯ä¸€ä½“ã§ä½œã‚Šã“ã‚“ã§ã—ã¾ã£ãŸã®ã§ã€ãŠã‹ã—ãªçŠ¶æ…‹ã«ãªã£ã¦ã„ã¾ã™ãŒã€å‹•ãã®ã§è‰¯ã—ã¨ã„ã†æ®µéšŽã§ã™ã€‚ ã“ã®å˜çœ¼ãƒ©ã‚¤ãƒ³ãƒˆãƒ¬ãƒ¼ã‚µã¯POMDPã®ä¾‹ã¨ã‚‚ã„ãˆã¾ã™ãŒã€ï¼ˆæœ€åˆã«ã‚³ãƒ¼ã‚¹ä¸Šã«ä¹—ã›ã‚‹å‰æã§ï¼‰ãƒã‚¸ãƒƒã‚¯ãƒ™ãƒ¼ã‚¹ã§å‹•ã‹ã—ã¦ã¿ã¦ã„る人ã¯å°‘ãªã‹ã‚‰ãšã„ã‚‹ã¨æ€ã„ã¾ã™ã€‚ POMDPã£ã¦ãªã‚“ãžã¨ã„ã†ã‹ãŸã¯ã€@okdshinã•ã‚“ãŒæœ€è¿‘親切ãªèª¬æ˜Žã‚’書ã‹ã‚Œã¦ã„ãŸã®ã§ã€å‚考ã«ã™ã‚‹ã¨ã„ã„ã¨æ€ã„ã¾ã™ã€‚ ⇒ 外部メモリ（External Memory）を利用ã—ãŸå¼·åŒ–å¦ç¿’ - Qiita 先述ã®ä»¥å‰ã®ãƒãƒ£ãƒ¬ãƒ³ã‚¸ã§ã¯ã€éŽåŽ»4ステップ分ã®ã‚¹ãƒ†ãƒ¼ãƒˆã‚’状態ã¨ã—ã¦DQNã«ãã‚Œã¦ã‚„ã£ã¦ã„ã¾ã—ãŸ
OpenAI Gymã§Qå¦ç¿’ã—ã¦ã¿ãŸ - The jonki
今更ãªãŒã‚‰OpenAI Gymã«æ‰‹ã‚’出ã—ã¦ã¿ã¾ã—ãŸï¼ŽOpenAI Gymã¯å¼·åŒ–å¦ç¿’ã®æ¤œè¨¼ãƒ—ラットフォームã§ã™ï¼Žè‰²ã€…ãªã‚²ãƒ¼ãƒ ãŒGymã¨ã—ã¦ã‚ã‚‹ã®ã§ï¼Œè‡ªåˆ†ã®ã‚¢ãƒ«ã‚´ãƒªã‚ºãƒ ã‚’ç°¡å˜ã«æ¤œè¨¼ã§ãã¾ã™ï¼Žä»¥å‰æœ€è‰¯çµŒè·¯ã‚’Qå¦ç¿’ã§æ±‚ã‚る記事を書ãã¾ã—ãŸãŒï¼ŒGymå‘ã‘ã«æ›¸ã‘ã°GUIも付ã„ã¦ãã¦é¢ç™½ã„ã§ã™ã—，コードをGistã§å…±æœ‰ã—ã¦ã„ã‚ã‚“ãªäººãŒè¦‹ã‚Œã‚‹ã®ãŒç´ 晴らã—ã„ã§ã™ã．OpenAI Gymã«ã¤ã„ã¦ã¯Qiitaãªã©ã®æ—¥æœ¬èªžè¨˜äº‹ã‚‚多ãã‚ã‚Šã¾ã™ãŒï¼Œå…¬å¼ãƒ‰ã‚ュメントをã•ã‚‰ã£ã¨ã‚„ã‚‹ã®ãŒè‰¯ã„ã¨æ€ã„ã¾ã™ï¼Žpipã§ç°¡å˜ã«å…¥ã‚Šã¾ã™ï¼Žã¾ãŸçµæžœã®ã‚¢ãƒƒãƒ—ãƒãƒ¼ãƒ‰æ³•ãªã©ã‚‚書ã„ã¦ã‚ã‚Šã¾ã™ï¼Ž OpenAI Gym Qå¦ç¿’ã§æœ€è‰¯çµŒè·¯ã‚’Pythonã§æ±‚ã‚ã¦ã¿ã‚‹ - The jonki ã“ã®è¨˜äº‹ã¯ç§ãŒDQNを勉強ã™ã‚‹ã«ã‚ãŸã£ã¦ã®å‹‰å¼·æ®µéšŽã®ãƒ¡ãƒ¢ã«ãªã‚Šã¾ã™ãŒï¼Œã›ã£ã‹ããªã®ã§è¨˜äº‹ã«ã—ã¦ãŠãã¾ã™ï¼Ž 今回やã‚ã†ã¨ã—ãŸã“ã¨ã¯ä¸‹è¨˜ã‚µã‚¤ãƒˆã•ã¾ã®å®Œå…¨ãªï¼’番煎ã˜ã§ã™ï¼Ž
OpenAI Gym を触ã£ã¦ã¿ã‚‹ - å£ã¯é€šã‚ŠæŠœã‘られã¾ã›ã‚“よ
OpenAI Gymãªã‚‹å¼·åŒ–å¦ç¿’用プラットフォームを触ã£ã¦ã¿ã¾ã—ãŸ(å‚考: PyConJPã®ãƒ—レゼンテーション)。 インストール自体ã¯pip install gymã§ä¸€ç™ºã§ã™(Atariゲームãªã©ã‚’扱ã„ãŸã„å ´åˆã¯pip install gym[atari]ã®ã‚ˆã†ã«ã‚µãƒ–パッケージをインストールã™ã‚‹å¿…è¦ãŒã‚るよã†ã§ã™)。一応ドã‚ュメントã§ä½¿ã„æ–¹ã¯èª¬æ˜Žã•ã‚Œã¦ã„ã¾ã™ãŒã€è‹¥å¹²æˆ¸æƒ‘ã†ç‚¹ãŒã‚ã£ãŸã®ã§éšæ™‚補足ã—ã¾ã™ã€‚ Atariゲームãªã©è‰²ã€…é¢ç™½ãã†ãªç’°å¢ƒãŒã‚ã‚Šã¾ã™ãŒã€ã¨ã‚Šã‚ãˆãšFrozenLake(4x4, 8x8)ã¨ã„ã†ã®ãŒåˆå¿ƒè€…å‘ã‘ã£ã½ã„ã®ã§ã€ã“れを試ã—ã¦ã¿ã¾ã—ãŸã€‚ ルールã¯éžå¸¸ã«å˜ç´”ã§ã€å›ºå®šé…ç½®ã®ãƒžãƒƒãƒ—上ã§ã‚¹ã‚¿ãƒ¼ãƒˆã‹ã‚‰ç©´ã«è½ã¡ãšã«ã‚´ãƒ¼ãƒ«ã«è¾¿ã‚Šç€ãã ã‘ã§ã™ã€‚æˆåŠŸæ™‚1点ã€å¤±æ•—時0点ã®å ±é…¬ãŒå¾—られã¾ã™ã€‚マップ上ã®è¨˜å·ã®æ„味ã¯ä»¥ä¸‹ã®é€šã‚Š: è¨˜å· æ„味 S スタート F 床 H ç©´ G ゴール ãŸã ã—スター
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Simple Reinforcement Learning with Tensorflow: Part 2 - Policy-based Agents
gym-cartpole/cartpole.py at 0788239f2c1be0b694a1b90a376780e1a8603bab · krocki/gym-cartpole
Policy Gradient to solve CartPole-v0 in OpenAI gym
ChristianHerta
Deep Q-Learning with Neural Networks (on Cart-Pole)
GitHub - nczempin/gym-tic-tac-toe: A simple two-player environment for openai/gym
GitHub - dennybritz/reinforcement-learning: Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
Simple reinforcement learning methods to learn CartPole
How can I use Docker without sudo?
basic_reinforcement_learning/tutorial3/README.md at master · vmayoral/basic_reinforcement_learning
OpenAI gym tutorial
Gym: A toolkit for developing and comparing reinforcement learning algorithms
[Python] Keras-RLã§ç°¡å˜ã«å¼·åŒ–å¦ç¿’(DQN)を試㙠- Qiita![[Python] Keras-RLã§ç°¡å˜ã«å¼·åŒ–å¦ç¿’(DQN)を試㙠- Qiita](https://cdn-ak-scissors.b.st-hatena.com/image/square/15b089e476fff5f50fa0b4baed1c33c676367c07/height=288;version=1;width=512/https%3A%2F%2Fqiita-user-contents.imgix.net%2Fhttps%253A%252F%252Fqiita-user-contents.imgix.net%252Fhttps%25253A%25252F%25252Fcdn.qiita.com%25252Fassets%25252Fpublic%25252Farticle-ogp-background-afbab5eb44e0b055cce1258705637a91.png%253Fixlib%253Drb-4.0.0%2526w%253D1200%2526blend64%253DaHR0cHM6Ly9xaWl0YS11c2VyLXByb2ZpbGUtaW1hZ2VzLmltZ2l4Lm5ldC9odHRwcyUzQSUyRiUyRnFpaXRhLWltYWdlLXN0b3JlLnMzLmFtYXpvbmF3cy5jb20lMkYwJTJGNjE0NjglMkZwcm9maWxlLWltYWdlcyUyRjE0NzM2OTU2NjQ_aXhsaWI9cmItNC4wLjAmYXI9MSUzQTEmZml0PWNyb3AmbWFzaz1lbGxpcHNlJmZtPXBuZzMyJnM9ZWE0NWMzNTIzOTlkMDdjMjFmNTZlNGJkMzE2OTk1NWY%2526blend-x%253D120%2526blend-y%253D467%2526blend-w%253D82%2526blend-h%253D82%2526blend-mode%253Dnormal%2526s%253Df86bbceb36a2b1fb9e87276eb69a5313%3Fixlib%3Drb-4.0.0%26w%3D1200%26fm%3Djpg%26mark64%3DaHR0cHM6Ly9xaWl0YS11c2VyLWNvbnRlbnRzLmltZ2l4Lm5ldC9-dGV4dD9peGxpYj1yYi00LjAuMCZ3PTk2MCZoPTMyNCZ0eHQ9JTVCUHl0aG9uJTVEJTIwS2VyYXMtUkwlRTMlODElQTclRTclQjAlQTElRTUlOEQlOTglRTMlODElQUIlRTUlQkMlQjclRTUlOEMlOTYlRTUlQUQlQTYlRTclQkYlOTIlMjhEUU4lMjklRTMlODIlOTIlRTglQTklQTYlRTMlODElOTkmdHh0LWFsaWduPWxlZnQlMkN0b3AmdHh0LWNvbG9yPSUyMzFFMjEyMSZ0eHQtZm9udD1IaXJhZ2lubyUyMFNhbnMlMjBXNiZ0eHQtc2l6ZT01NiZ0eHQtcGFkPTAmcz0wODM0YWU3M2ZiY2M2MGNkY2YxNWE2ZDViMjA4YmMwMw%26mark-x%3D120%26mark-y%3D112%26blend64%3DaHR0cHM6Ly9xaWl0YS11c2VyLWNvbnRlbnRzLmltZ2l4Lm5ldC9-dGV4dD9peGxpYj1yYi00LjAuMCZ3PTgzOCZoPTU4JnR4dD0lNDBpbm9vcnkmdHh0LWNvbG9yPSUyMzFFMjEyMSZ0eHQtZm9udD1IaXJhZ2lubyUyMFNhbnMlMjBXNiZ0eHQtc2l6ZT0zNiZ0eHQtcGFkPTAmcz0xZjk5MjgyMmJlYjBlNjM4NzllZDcyZjJmMDY3YjBhMA%26blend-x%3D242%26blend-y%3D480%26blend-w%3D838%26blend-h%3D46%26blend-fit%3Dcrop%26blend-crop%3Dleft%252Cbottom%26blend-mode%3Dnormal%26s%3Dafc04e9ffc07203caafac1d3f97f9bd1)
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