The slides of Artificial Intelligence and Entertainment Science (AIES) Workshop 2021 Keynote lecture
https://aies.info/program/
Empathic Entertainment in Digital Game
A digital game give a unique experience to a user. AI system in Digital game consists of three kinds of AI such as Meta-AI, Character AI, and Spatial AI. Game experience is formed by them. Meta-AI keeps watching a status of game and controlling characters, objects, terrain, weather and so on dynamically to make many dramatic and empathic situations in a game for users. Character AI is a brain of an autonomous game character to make a decision by itself, but sometimes it acts to achieve a goal issued from Meta-AI. Spatial AI analyses a terrain and abstracts its features to communicate them to Meta-AI and Character-AI. They can make their intelligent decisions by using specific terrain and environment features. The AI system is called MCS-AI dynamic cooperative model (Meta-AI, Character AI, and Spatial AI dynamic cooperative model). In the lecture, I will explain the system by showing some cases of published digital games.
37. DQNによるアタリゲーム学習過程
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Alex Graves,
Ioannis Antonoglou, Daan Wierstra, Martin Riedmiller (DeepMind Technologies)
Playing Atari with Deep Reinforcement Learning
http://www.cs.toronto.edu/~vmnih/docs/dqn.pdf
https://www.youtube.com/watch?v=5WXVJ1A0k6Q
38. • Pπ ロールアウトポリシー(ロールアウトで討つ手を決める。Pπ(a|s) sという状態でaを討つ確率)
• Pσ Supervised Learning Network プロの討つ手からその手を討つ確率を決める。Pσ(a|s)sという状態でaを討
つ確率。
• Pρ 強化学習ネットワーク。Pρ(学習済み)に初期化。
• Vθ(s’) 局面の状態 S’ を見たときに、勝敗の確率を予測する関数。つまり、勝つか、負けるかを返します。
Mastering the game of Go with deep neural networks and tree search
http://www.nature.com/nature/journal/v529/n7587/full/nature16961.html
https://deepmind.com/research/alphago/
DEEP MIND社:DQNによるアタリゲーム学習過程
39. Deep Mind社 「Agent 57」
• Atariの古典的なゲーム57個を人間よりうまくプレイできるよう
になった Deep Mind社のAI
• https://deepmind.com/blog/article/Agent57-Outperforming-
the-human-Atari-benchmark
48. Enhancing Game Experiences with Character AI
Andrew Moran, Jordan Carlton(Magic Leap, Magic Leap/Weta Workshop)
https://gdcvault.com/play/1025829/Magic-Leap-Enhancing-Game-Experiences
49. Enhancing Game Experiences with Character AI
Andrew Moran, Jordan Carlton(Magic Leap, Magic Leap/Weta Workshop)
https://gdcvault.com/play/1025829/Magic-Leap-Enhancing-Game-Experiences
74. Deep Mind: Capture the flag
• Deep Mind社が行っている「旗取りゲーム」のプラットフォーム
• 現在は人間よりも圧倒的に強くなってしまった
• 人間が見つけた戦略を、AIがみつけている
• Quake III のエンジンを使用
• マップは自動生成
Deep Mind: Capture the Flag: the emergence of complex cooperative agents
https://deepmind.com/blog/article/capture-the-flag-science
75. • https://deepmind.com/blog
/capture-the-flag/
• Multi agnet learning
Deep Mind: Capture the Flag: the emergence of complex cooperative agents
https://deepmind.com/blog/article/capture-the-flag-science
Deep Mind: Capture the flag
76. Two Agent Cooperation by DeepMind
Deep Mind: Capture the Flag: the emergence of complex cooperative agents
https://deepmind.com/blog/article/capture-the-flag-science
77. Deep Mind: Capture the flag
Deep Mind: Capture the Flag: the emergence of complex cooperative agents
https://deepmind.com/blog/article/capture-the-flag-science
87. Microsoft: TextWorld
• マイクロソフトが構築したテキストアドベンチャーの学習環境
• 50ほどのテキストアドベンチャーを内包している
• TextWorld: A Learning Environment for Text-based Games
• https://arxiv.org/abs/1806.11532
•
• TextWorld: A learning environment for training reinforcement learning agents,
inspired by text-based games
• https://www.microsoft.com/en-us/research/blog/textworld-a-learning-
environment-for-training-reinforcement-learning-agents-inspired-by-text-
based-games/
•
• Getting Started with TextWorld
• https://www.youtube.com/watch?v=WVIIigrPUJs
96. Assassin’s Creed Origin の事例
• スクリプトによるオブジェクト同士の干渉テスト
• キャラクターの生成ポイントと配置オブジェクトの干渉テスト
• スクリプトによるテスト
'Assassin's Creed Origins': Monitoring and Validation of World Design Data
Nicholas Routhier
Ubisoft Montreal
http://www.gdcvault.com/play/1025054/-Assassin-s-Creed-Origins
102. Deep Learning: Beyond the Hype, Magnus Nordin Electronic Arts
https://www.gdcvault.com/play/1025098/Deep-Learning-Beyond-the
EA SEED
https://www.ea.com/seed/news/seed-imitation-learning-concurrent-actions
https://www.ea.com/seed/news/self-learning-agents-play-bf1
AIエージェントに「バトルフィールド 1」のプレイを教えるには?
https://www.ea.com/ja-jp/news/teaching-ai-agents-battlefield-1
Experimental Self-Learning AI in Battlefield 1
https://www.youtube.com/watch?v=ZZsSx6kAi6Y
Deep Learning in Battlefield One
103. Deep Learning in Battlefield One
https://www.ea.com/seed/news/seed-imitation-learning-concurrent-actions
https://www.ea.com/seed/news/self-learning-agents-play-bf1
https://www.youtube.com/watch?v=ZZsSx6kAi6Y
Deep Learning: Beyond the Hype, Magnus Nordin Electronic Arts
https://www.gdcvault.com/play/1025098/Deep-Learning-Beyond-the
EA SEED
https://www.ea.com/seed/news/seed-imitation-learning-concurrent-actions
https://www.ea.com/seed/news/self-learning-agents-play-bf1