由智慧如光談發現與覆蓋，可變空間決策問題的數學模式

Effective Decision Making in Changeable Spaces: Discovering and Covering Models

本篇由習慣領域探討可變空間決策問題的數學模式：「發現與覆蓋」模式的架構與分析。我們由智慧如光的角度切入，討論決策盲點和決策陷阱的成因，以及如何避免盲點與陷阱的方法。本文所探討的可變空間決策模型結合了人類心理與行為的動態，也考慮了不同決策參數的重新結構。它的基礎乃源於習慣領域理論，而其基本組成元件除了決策參數（包含決策要素與決策環境）之外，還包括習慣領域三大工具箱裏的各項方法，以及能力集合分析的概念。它是一個有別於傳統決策理論與最佳化方法的全新架構，將有助於決策者與管理者在面對現實世界裏的挑戰性問題時，重新思維，增強其智慧之光，更成功有效地處理決策問題，避免陷入盲點與陷阱。

Decision wisdom likes mental light shining into the dark of the problem. Using this concept， in this paper， we focus on modeling discovering and covering as a main tool for effective decision making in changeable spaces problems， and propose a new decision making/ optimization paradigm， the optimization in changeable spaces (OCS). The unique feature of this proposed model of decision making in changeable spaces is that it incorporates human psychology and its dynamics as part of the decision making process and allows the restructuring of the decision parameters. Based on Habitual Domain theory， the decision parameters， the concept ofcompetence set and the mental operators 7-8-9 principles of deep knowledge， the model provides decision makers， managers and executives a new framework to reduce decision blinds and avoid decision traps as to solve challenging decision problems in changeable spaces effectively and efficiently.