A Review of Time Critical Decision Making Models and Human Cognitive Processes

Azuma, Ronald; Daily, M.; Furmanski, Chris

doi:10.1109/aero.2006.1656041

Cited by 37 publications

(27 citation statements)

References 21 publications

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“…It can be shown that such irrational decision making behaviors are actually rational when considering the broader decision making process model presented in this paper. Several studies have shown the need for developing decision making models based on the human cognitive processes; for example see Azuma et al (2006) and Endsley et al (2007). The model developed in this paper also considers the human cognitive processes.…”

Section: Introductionmentioning

confidence: 99%

Decision making process: typology, intelligence, and optimization

Malakooti

2010

J Intell Manuf

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Decision making is concerned with evaluating and/or ranking possible alternatives of action. In this paper, we develop a model for the process of decision making. Understanding the decision process can provide insights into how humans make decisions, understand their decision making approaches, and how they differ from each other. We believe that decision makers who are conscious of their decision process types can make more effective and balanced decisions. In this paper, we present a new decision process model based on the following four dimensions where each dimension is defined by two opposing types: Information Processing (Concrete and Abstract), Alternative Generation (Adaptive and Constructive), Alternative Evaluation (Moderate and Bold), and Decision Closure (Organized and Flexible). Furthermore, an approach for assessing each of the four decision process types by a mathematical function is presented. In a much boarder scope than decision making, these assessed functions can be used to evaluate and rank alternatives. The decision process model can also be used in conjunction with multiple criteria decision making and multiple objective optimization. The model can also be used to explain the reasons that the classical decision making models fail to describe real decision makers' behavior, and mistakenly label such behavior as irrational. The proposed decision process model can be used for developing new behavioral, rational, and intelligent decision making theories and approaches. Extensions of this work may include group decision making, organizational decision making, team formation, and risk behavior analysis. Experimental results of over four hundred engineering students are reported. A web site has been developed for users (http://car.cwru.edu/decision/). KeywordsDecision behavior · Intelligent decision making · Multi-dimensional decision process · Dynamic decision making · Irrational decision making · Multiple criteria decision making · Multiple objective optimization IntroductionThe process of decision making is multi-faceted and involved. At times this process occurs naturally and spontaneously; at other times, it may be intricately planned with much forethought. There are many factors that contribute to this process including personality attributes, temperaments, past experiences, and external factors. Decision making is the most complex human behavior. In order to improve the effectiveness of decision making, we have developed a new model for characterizing the decision making process and how different people make different decisions. We provide a set of characteristics for identifying decision making types. Understanding these types helps decision makers understand and be aware of their own preferential decision making behaviors versus those of others. In the context of decision making, "Know thyself" is about becoming more conscious about how one makes decisions. It helps one to find a model that can closely describe the decision maker's behavior. By knowing the processes of decision making and...

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Section: Introductionmentioning

confidence: 99%

Decision making process: typology, intelligence, and optimization

Malakooti

2010

J Intell Manuf

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“…The model also suggests that humans make quick decisions in such situations by matching the current situation with past experiences and selecting solutions to similar situations. Similar ideas were also advocated in [10,15,16].…”

Section: Related Workmentioning

confidence: 56%

Dealing with dynamic changes in time critical decision‐making for MOUT simulations

Ting

Zhou

2009

Computer Animation & Virtual

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Generating realistic behaviors for the non-player characters (also known as bots) is an important task for Military Operations on Urban Terrain (MOUT) simulations. Most of the current bots reasoning models are based on complete rational analysis of all alternatives. However, such models may not be adequate in time critical and uncertain situations. In such situations, due to time constraints and incomplete information, humans rely mainly on experience rather than some structured analysis of the given situation to make decisions. In our previous work, we have developed SNAP, a time critical decision-making framework which aims to imitate human decision-making processes for MOUT simulations. A major limitation that we found about SNAP is its difficulty in dealing with dynamic changes in MOUT simulations. In this paper, we propose to address this problem by incorporating a novel feature of expectations into SNAP. The effectiveness of this new feature is assessed with Twilight City, a virtual environment for MOUT simulations. Experimental results show that our expectation model works well in dealing with dynamic changes in MOUT.

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“…Pada proses pemecahan masalah, individu menggunakan pengetahuan dan penalaran untuk memutuskan apa yang harus dilakukan, menyimpulkan cara terbaik dalam mencapai tujuan dan menentukan konsekuensi dari keyakinan tindakan yang diambil [7] [13]. Dalam praktiknya, salah satu komponen penting pendukung proses pemecahan masalah adalah dengan mengingat pengalaman sebelumnya pada situasi yang sama [14] [15].…”

Section: Pendahuluanunclassified

Kajian Model Pembelajaran: Pendekatan Cognitive Apprenticeship Model Case Based Reasoning Dalam Pembelajaran Matematika

Oktaviyanthi¹

2017

Preprint

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Abstrak. Penalaran adaptif dan pengambilan keputusan merupakan kemampuan yang menjadi bahasan pada perkembangan kognitif dan merupakan dua kemampuan penentu dalam proses pemecahan masalah. Untuk itu membelajarkan kedua kemampuan kognitif tersebut pada peserta didik merupakan tugas guru yang perlu diupayakan sedini dan sebaik mungkin. PENDAHULUANBelajar matematika merupakan proses kompleks yang dalam perkembangannya hingga saat ini para ahli pendidikan matematika melalui kajian dan penelitian terus mencari dan memperbaharui metode-metode yang efektif dan efisien tentang bagaimana membelajarkan matematika tanpa mengabaikan kondisi dan karakteristik peserta didik dan tanpa mengurangi esensi dari matematika itu sendiri. Telah menjadi keumuman bersama bahwa belajar matematika lebih dari sekedar pengetahuan keterampilan dan prosedur. Tujuan dari pembelajaran matematika jauh melampaui pembentukan keterampilan mekanik. Wacana penting mengenai peserta didik dalam pembelajaran matematika yaitu bagaimana mereka menjadi individu yang mahir matematika. Kemahiran matematika tidak hanya bermanfaat dalam proses pencapaian akademik peserta didik di pendidikan formal, melainkan salah satu aspek yang digunakan dalam memecahkan masalah di kehidupan nyata ketika peserta didik berinteraksi dengan lingkungan. Sullivan, P. (2011) menekankan pentingnya memahirkan peserta didik dengan matematika melalui pandangan dasar terhadap pendidikan matematika yaitu (1) functional yang memandang ilmu matematika dapat melengkapi kebutuhan peserta didik di masa depan, dan (2) specialist yang memandang ilmu matematika diperlukan bagi peserta didik yang akan mendalami matematika sebagai studi lanjut atau suatu profesi [1].Namun untuk memahirkan matematika pada peserta didik bukan merupakan hal mudah. Dalam konteks penggunaan matematik dalam kehidupan nyata, fakta yang terungkap dari hasil penelitian bahwa peserta didik masih mengalami kesulitan untuk melihat bagaimana aljabar, geometri trigonometri, kalkulus atau materi matematika lainnya dapat membantu mereka dalam

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A Review of Time Critical Decision Making Models and Human Cognitive Processes

Cited by 37 publications

References 21 publications

Decision making process: typology, intelligence, and optimization

Decision making process: typology, intelligence, and optimization

Dealing with dynamic changes in time critical decision‐making for MOUT simulations

Kajian Model Pembelajaran: Pendekatan Cognitive Apprenticeship Model Case Based Reasoning Dalam Pembelajaran Matematika

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