VIDEO GAME PROCESSING PROGRAM, VIDEO GAME PROCESSING DEVICE, VIDEO GAME PROCESSING METHOD, AND PROGRAM FOR LEARNING

To increase a learning speed on AI using an image drawing a virtual space as a photographed image from a viewpoint of a character for action determination of the character.SOLUTION: A video game processing program executes a learning mode in which a character is caused to execute an action determine...

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Hauptverfasser: OTANI TOMOKAZU, MIYAKE YOICHIRO
Format: Patent
Sprache:eng ; jpn
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Zusammenfassung:To increase a learning speed on AI using an image drawing a virtual space as a photographed image from a viewpoint of a character for action determination of the character.SOLUTION: A video game processing program executes a learning mode in which a character is caused to execute an action determined by AI, and work on an assignment of a video game, and the result of the assignment is used for learning of the AI; generates a low quality image drawing a virtual space where the assignment is being executed as a photographed image from a specific viewpoint with low image quality settings; inputs the low quality image to a neural network composed to output an appropriate action content from options for determining the action of the character with the low quality image in which the assignment is being executed as input, and determines the action content of the character; executes input of the action content determined for the character working on the assignment; and executes an evaluation based on a predetermined evaluation criterion on a degree of assignment achievement of the character, and updates the weight and/or bias of the neural network based on the evaluation result.SELECTED DRAWING: Figure 1 【課題】仮想空間をキャラクタの視点からの撮影画像として描画した画像をキャラクタの行動決定に用いるAIについて、学習の高速化を実現する。【解決手段】AIが決定した行動をキャラクタに実行させてビデオゲームの課題に取り組ませて課題の結果を当該AIの学習に利用する学習モードを実行し、課題実行中の仮想空間について低画質な設定にて特定視点からの撮影画像として描画した低画質画像を生成し、課題実行中の低画質画像を入力としてキャラクタの行動決定のための選択肢の中から適切な行動内容を出力することを目的として構成されたニューラルネットワークに対して低画質画像を入力してキャラクタの行動内容を決定し、課題に取組中のキャラクタに対して決定した行動内容の入力を実行し、キャラクタの課題の達成度について所定の評価基準に基づいて評価を行い、評価結果に基づいてニューラルネットワークの重み及び/又はバイアスの更新を実行する。【選択図】図1