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汎用人工知能実現に向けた人とエージェントの相互適応の研究 (本文)

大澤, 正彦 慶應義塾大学

2020.03.23

概要

1.1 汎用人工知能
(Artificial General Intelligence: AGI)
世界中でヒトレベルの汎用人工知能の実現への期待が高まっている[8].汎用人工知能(Artificial General Intelligence: AGI)[53, 58, 55] とは,特定のタスクのために設計されたわけでなく,環境に応じて汎用的に動作可能な人工知能である.一般に,特定のタスクに向けて設計された人工知能を特化型人工知能(narrow AI)[163] と呼ぶ.AGI は,narrow AI の対立的な概念といえる.

AGI への期待が高まった背景には,深層学習(Deep Learning)[103, 59]の成功が大きな要因として挙げられる.深層学習を用いたシステムは,囲碁や将棋に代表されるゲーム[122, 187, 189, 188],画像認識[164],自然言語処理[18, 40] といった分野で人と同等以上の性能を発揮している.こ れまで人を超える性能を発揮したシステムは全てnarrow AI であるといえるが,深層学習自体が多くのドメインに適用可能であることからも,現代の人工知能研究の発展の先にヒトレベルのAGI 実現が想像されている.

実際にヒトレベルのAGI が実現した場合の影響についても様々な考察がされている[75, 77, 115].特に経済的には,我々人類の生産性を急激に高めることにつながる[75, 77].もしも知的労働を代替できる存在になれば,より発展的な人工知能の開発を含むあらゆる研究開発を人工知能が担い自動化される可能性もあるという意味で,ヒトレベルの AGI は人類最後の発明になるとも考えられている.

本研究の目的は,ヒトレベルのAGI の実現を目指す一連の研究に新たな方向性を与えることにある.具体的には,次節で説明する現在直面しているAGI 開発の困難さを解消するために,AGI として多くの人に認められることを目標とした新たな研究アプローチを提案する.

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