JP2022523337A - 人工知能による混沌としたシステムの異常への対応 - Google Patents
人工知能による混沌としたシステムの異常への対応 Download PDFInfo
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Abstract
Description
ここで、s(t)はタイムウィンドウtでのセンサ読取値である。小文字のシグマは、ボラティリティ推定量、すなわち、バイパワーバリエーションによって計算されたセンサデータにおける標準偏差の類似形を表す。
Claims (20)
- 混沌とした環境における異常を検出して対応するための人工知能システムであって:
1つ又は複数の自律エージェントデバイスと;
プロセッサと、命令を格納する非一時的なメモリと、を備える中央サーバと;を備え、
前記命令は、前記プロセッサによって実行されたときに、前記プロセッサが:
第1のタイムウィンドウの間に、1つ又は複数のリモート電子センサから、前記混沌とした環境における1つ又は複数の変数の疑似ブラウン変化を記録したセンサ読取値の第1のセットを受信し;
前記センサ読取値の第1のセットに基づいて、前記第1のタイムウィンドウの後の第2のタイムウィンドウの間に、前記1つ又は複数の変数の予想範囲を決定し;
前記第2のタイムウィンドウの間に、前記1つ又は複数のリモート電子センサから、前記1つ又は複数の変数の変化を記録したセンサ読取値の第2のセットを受信し;
前記センサ読取値の第2のセットに基づいて、前記1つ又は複数の変数のうちの1つの変数が前記予想範囲内にないことを判定し;
前記1つ又は複数の自律エージェントデバイスに、前記1つの変数が予想範囲外にあることによって示される潜在的な害を軽減するように試行させる;ようにする、
システム。 - 前記予想範囲を決定することは、少なくとも部分的には、前記第1のタイムウィンドウ内の時間の一部におけるセンサ読取値から計算されたバイパワーバリエーションに基づく、
請求項1に記載のシステム。 - 前記予想範囲を決定することは、少なくとも部分的には、前記混沌とした環境においてアクティブな干渉のない場合には、センサ読取値が少なくとも所定の確率で前記予想範囲内に収まるような前記所定の確率に基づく、
請求項1に記載のシステム。 - 前記1つ又は複数の自律エージェントデバイスは、ネットワークメッセージがネットワークを介して送信されないようにすることによって、前記潜在的な害を軽減するように試行する、
請求項1に記載のシステム。 - 前記1つ又は複数の自律エージェントデバイスは、前記混沌とした環境に作用する物理アプライアンスをアクティブ化することによって、前記潜在的な害を軽減するように試行する、
請求項1に記載のシステム。 - 前記1つ又は複数の自律エージェントデバイスは、自律車両を特定の場所へ移動させることによって、前記潜在的な害を軽減するように試行する、
請求項1に記載のシステム。 - 前記1つ又は複数の自律エージェントデバイスは、ヒューマンユーザが受信するためのメッセージを生成することによって、前記潜在的な害を軽減するように試行する、
請求項1に記載のシステム。 - 前記1つ又は複数の自律エージェントデバイスは、ヒューマンユーザに可視又は可聴であるアラームのアクティブ化によって、前記潜在的な害を軽減するように試行する、
請求項1に記載のシステム。 - 前記命令は、前記プロセッサによって実行されたときに、前記プロセッサが、更に:前記予想範囲内にない前記1つ又は複数の変数に少なくとも部分的に基づいて前記予想範囲を拡大する;ようにする、
請求項1に記載のシステム。 - 前記命令は、前記プロセッサによって実行されたときに、前記プロセッサが、更に:前記1つ又は複数の変数が前記予想範囲内にあることを示すセンサ読取値の第3のセットに少なくとも部分的に基づいて、前記予想範囲を狭める;ようにする、
請求項1に記載のシステム。 - 混沌とした環境における異常を検出して対応するための人工知能の方法であって:
第1のタイムウィンドウの間に、1つ又は複数のリモート電子センサから、前記混沌とした環境における1つ又は複数の変数の疑似ブラウン変化を記録したセンサ読取値の第1のセットを受信するステップと;
前記センサ読取値の第1のセットに基づいて、前記第1のタイムウィンドウの後の第2のタイムウィンドウの間に、前記1つ又は複数の変数の予想範囲を決定するステップと;
前記第2のタイムウィンドウの間に、前記1つ又は複数のリモート電子センサから、前記1つ又は複数の変数の変化を記録したセンサ読取値の第2のセットを受信するステップと;
前記センサ読取値の第2のセットに基づいて、前記1つ又は複数の変数のうちの1つの変数が前記予想範囲内にないことを判定するステップと;
前記1つ又は複数の自律エージェントデバイスに、前記1つの変数が予想範囲外にあることによって示される潜在的な害を軽減するように試行させるステップと;を備える、
方法。 - 前記予想範囲を決定することは、少なくとも部分的には、前記第1のタイムウィンドウ内の時間の一部におけるセンサ読取値から計算されたバイパワーバリエーションに基づく、
請求項11に記載の方法。 - 前記予想範囲を決定することは、少なくとも部分的には、前記混沌とした環境においてアクティブな干渉のない場合には、センサ読取値が少なくとも所定の確率で前記予想範囲内に収まるような前記所定の確率に基づく、
請求項11に記載の方法。 - 前記1つ又は複数の自律エージェントデバイスは、ネットワークメッセージがネットワークを介して送信されないようにすることによって、前記潜在的な害を軽減するように試行する、
請求項11に記載の方法。 - 前記1つ又は複数の自律エージェントデバイスは、前記混沌とした環境に作用する物理アプライアンスをアクティブ化することによって、前記潜在的な害を軽減するように試行する、
請求項11に記載の方法。 - 前記1つ又は複数の自律エージェントデバイスは、自律車両を特定の場所へ移動させることによって、前記潜在的な害を軽減するように試行する、
請求項11に記載の方法。 - 前記1つ又は複数の自律エージェントデバイスは、ヒューマンユーザが受信するためのメッセージを生成することによって、前記潜在的な害を軽減するように試行する、
請求項11に記載の方法。 - 前記1つ又は複数の自律エージェントデバイスは、ヒューマンユーザに可視又は可聴であるアラームのアクティブ化によって、前記潜在的な害を軽減するように試行する、
請求項11に記載の方法。 - 前記予想範囲内にない前記1つ又は複数の変数に少なくとも部分的に基づいて前記予想範囲を拡大するステップを更に備える、
請求項11に記載の方法。 - 前記1つ又は複数の変数が前記予想範囲内にあることを示すセンサ読取値の第3のセットに少なくとも部分的に基づいて、前記予想範囲を狭めるステップを更に備える、
請求項11に記載の方法。
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US16/264,671 US10901375B2 (en) | 2019-01-31 | 2019-01-31 | Chaotic system anomaly response by artificial intelligence |
PCT/US2020/015932 WO2020160301A1 (en) | 2019-01-31 | 2020-01-30 | Chaotic system anomaly response by artificial intelligence |
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