建立“可調適的智慧環境”，意謂在建築環境中建立具有可調適能力的系統或者是機制，它具備人工智慧、能夠自主性的根據環境的動態改變或者使用者即時的需求，作用彈性的行為模式或者提供適當的控制條件，以滿足可調適機制的設計目標。感測器、運算科技與網際網路技術的進展，使得智慧住宅的設計成為一個重要的研究方向。然而，”如何建立可調適的智慧環境以滿足使用者的生活需求？”成為空間智慧化的重要課題。

本論文以“智慧皮層”作為建立“可調適的智慧環境”的研究範例，智慧皮層假設：如果建築的外殼具有智慧，那麼它必需同時能夠考量“環境”與“使用者”的變化與需求，並且以三項相關理論作為整合的關鍵要素，包括：（1）智慧代理者、（2）涵構覺察與（3）模糊理論（包括模糊邏輯與類神經模糊）。 “智慧代理者”為具有自主性的人工智慧電腦程式，亦作為運算與資訊溝通機制的知識再現工具。一個具備“涵構覺察”的系統是說它能夠萃取、詮釋與使用涵構的資訊，並且調適它的機能，提供給使用者或者所從事的任務所應用。藉由“模糊邏輯”，智慧代理者能夠主動的推論與偵測不同的情境，作出最佳化的決定，並且經由“類神經模糊”的學習機制，能夠調適其機能以符合環境與使用者的變化與需求。因此，智慧皮層 以智慧代理者作為動態的反應使用者需求與環境對應的機制，涵構覺察作為智慧代理者的機能，並且以模糊理論建立其判斷與反應的控制條件。

藉著文獻回顧、課題研究、案例分析與歸納條件，本研究確立了可調適環境的研究範疇；建立以智慧代理者理論建立可調適性環境的前提假設；歸納與分析諸多智慧代理者可行的運算機制與選擇的條件。並且透過智慧皮層的原型建構；設計實驗與進行測試與評估，建立了環境、使用者與智慧皮層的對應關係。

根據智慧皮層原型的建立、測試與評估，研究發現建立以“智慧代理者”為基礎的“智慧住宅”，能夠在分散式的智慧環境裡，提供比中央控制的智慧系統，更具自主性、彈性的可調適能力。在符合環境永續原則下，它除了能夠合理推論、可以經由學習與調適提供使用者更佳的生活條件與互動模式、並且能夠協同合作，共同完成設計的目標。藉著自主性的可調適行動，智慧皮層消除過多和過於複雜的人機介面。而模糊推論結合了規則基礎的邏輯推論以強化智慧化系統的合理性；模糊理論結合類神經的學習演算以強調系統可靠的預測能力。所以智慧代理者為基礎的智慧住宅強調以使用者經驗為導向的涵構覺察機能，促進更舒適、安全與健康的居家生活。

The establishment of an "adaptive smart environment" implies the establishment of systems or mechanisms with adaptive ability in the architectural environment. These systems or mechanisms possess artificial intelligence and can autonomously change in accordance with the state of to environment or the occupant's immediate needs, implementing flexible behavioral models or providing appropriate control conditions satisfying the system's or mechanism's design goals. Progress and development in sensor, computing, and Internet technology have made the design of smart houses an important research paradigm. Although improvement of architectural environmental quality must be linked with the environment and occupants' needs, the question of "how to establish an adaptive smart environment able to satisfy occupants' everyday needs?" has become a major issue in the design of smart spaces.

This study takes a house's envelop as an example, and analyzes the feasibility of a smart skin. The three theoretical aspects of (1) intelligent agents, (2) context-awareness, and (3) fuzzy theory are used as key integrating elements. "Intelligent agents" are AI computer programs possessing autonomy, and serve as knowledge representation tools for operating and information communication mechanisms. A "context-aware" system is able to extract, interpret, and use contextual information, adjust system functions, and provide information to users or applications performing tasks. Intelligent agents can use "fuzzy logic" to actively deduce and detect various situations, enabling them to make optimal decisions. "Neuro-fuzzy" learning mechanisms can adjust system functions to adapt to the needs and changes of the environment and users. This study therefore proposes that intelligent agents be used as a mechanism for dynamically responding to users' needs and environmental changes; the intelligent agents have the function of "context-awareness"; and fuzzy theory be used to establish judgment and response control conditions.

This study relies on a review of the literature, topical research, case analysis, and summary of conditions to establish adaptive environment research issues, uses intelligent agent theory to derive environmental assumptions for adaptive houses, constructs a smart skin prototype, designs experiments, and tests and assesses the relationship between the smart skin and the environment.

This study discovered that an agent-based smart house can provide more autonomous and flexible adaptation than a centrally-controlled smart system. In line with the principle of environmental sustainability, agent-based smart houses can make reasonable assumptions, and can also use learning and adaptation to provide users with better living conditions and interaction options. They can further cooperate with users in jointly achieving design goals. Autonomous adaptive behavior enables smart skins to do away with numerous, excessively complex user interfaces. Rule-based fuzzy reasoning and neuro fuzzy learning algorithms can improve the rationality, reliability, and prediction ability of a smart system. As a consequence, an intelligent agent-based smart house with user experience-oriented context-awareness can provide a living environment promoting comfort, safety, and good health.

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