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商品描述
This volume addresses context from three comprehensive perspectives: first, its importance, the issues surrounding context, and its value in the laboratory and the field; second, the theory guiding the AI used to model its context; and third, its applications in the field (e.g., decision-making). This breadth poses a challenge. The book analyzes how the environment (context) influences human perception, cognition and action. While current books approach context narrowly, the major contribution of this book is to provide an in-depth review over a broad range of topics for a computational context no matter its breadth. The volume outlines numerous strategies and techniques from world-class scientists who have adapted their research to solve different problems with AI, in difficult environments and complex domains to address the many computational challenges posed by context.
Context can be clear, uncertain or an illusion. Clear contexts: A father praising his child; a trip to the post office to buy stamps; a policewoman asking for identification. Uncertain contexts: A sneak attack; a surprise witness in a courtroom; a shout of "Fire! Fire!" Contexts as illusion: Humans fall prey to illusions that machines do not (Adelson’s checkerboard illusion versus a photometer). Determining context is not easy when disagreement exists, interpretations vary, or uncertainty reigns. Physicists like Einstein (relativity), Bekenstein (holographs) and Rovelli (universe) have written that reality is not what we commonly believe. Even outside of awareness, individuals act differently whether alone or in teams.
Can computational context with AI adapt to clear and uncertain contexts, to change over time, and to individuals, machines or robots as well as to teams? If a program automatically "knows" the context that improves performance or decisions, does it matter whether context is clear, uncertain or illusory? Written and edited by world class leaders from across the field of autonomous systems research, this volume carefully considers the computational systems being constructed to determine context for individual agents or teams, the challenges they face, and the advances they expect for the science of context.
商品描述(中文翻譯)
本卷從三個全面的角度探討上下文：首先，它的重要性、圍繞上下文的問題以及它在實驗室和現場的價值；其次，指導用於建模其上下文的人工智慧理論；第三，它在現場的應用（例如，決策）。這種廣度帶來了挑戰。本書分析環境（上下文）如何影響人類的感知、認知和行動。雖然目前的書籍對上下文的探討較為狹隘，但本書的主要貢獻在於提供對計算上下文的廣泛主題的深入回顧，無論其範圍如何。本卷概述了來自世界級科學家的眾多策略和技術，他們已經調整自己的研究以解決不同問題，利用人工智慧在困難的環境和複雜的領域中應對上下文所帶來的許多計算挑戰。
上下文可以是清晰的、不確定的或是一種幻覺。**清晰的上下文**：一位父親讚美他的孩子；一次去郵局買郵票的旅行；一位女警要求出示身份證明。**不確定的上下文**：一次突襲；法庭上的驚喜證人；一聲「火！火！」的呼喊。**作為幻覺的上下文**：人類會受到機器不會受到的幻覺的影響（阿德爾森的棋盤幻覺與光度計）。當存在分歧、解釋各異或不確定性主導時，確定上下文並不容易。像愛因斯坦（相對論）、貝肯斯坦（全息圖）和羅維利（宇宙）等物理學家曾寫道，現實並不是我們通常所相信的樣子。即使在無意識的情況下，個體在獨自或團隊中行動的方式也會有所不同。
計算上下文與人工智慧能否適應清晰和不確定的上下文，隨著時間的推移而變化，並適應個體、機器或機器人以及團隊？如果一個程序自動「知道」能改善性能或決策的上下文，那麼上下文是清晰的、不確定的還是虛幻的，這是否重要？本卷由來自自主系統研究領域的世界級領導者撰寫和編輯，仔細考慮了正在構建的計算系統，以確定個體代理或團隊的上下文、他們面臨的挑戰以及他們對上下文科學的期望進展。
