Decision Making Based on Ill-Known Decision Trees

Kód výsledku v IS VaVaI

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Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Decision Making Based on Ill-Known Decision Trees

Popis výsledku v původním jazyce

IB (Insolvency and Bankruptcy) tasks are ill-known processes. Real life decision making related to IB is based on common sense reasoning only. To formalise such vague, sparse, partially inconsistent and subjective tasks as IB classical decision making trees can be used. However, traditional evaluation of these trees requires a complete set of relevant numerical values. These values are often either prohibitively inaccurate or they are unknown as they are unique. Moreover, decision economists dealing with IBs are usually not willing to invest too much time into study of complex mathematical theories. IB problem is transferred into a decision making tree which indicates all sub-decisions and random lotteries. Random lotteries quantifies such sub-IBs events which are not certain. Such decision trees are evaluated using well known methods. However, the required data sets are often incomplete. The problem of missing data items is solved by introducing a simple and generally applicable heuristic – a longer sequence of events is less probable. A company has legislatively supported several options how to deal with bankruptcy situation. Each of the option can be solved in three different ways by using decision–making tree as tool for probability determination, using already known probabilities from previous case.

Název v anglickém jazyce

Decision Making Based on Ill-Known Decision Trees

Popis výsledku anglicky

IB (Insolvency and Bankruptcy) tasks are ill-known processes. Real life decision making related to IB is based on common sense reasoning only. To formalise such vague, sparse, partially inconsistent and subjective tasks as IB classical decision making trees can be used. However, traditional evaluation of these trees requires a complete set of relevant numerical values. These values are often either prohibitively inaccurate or they are unknown as they are unique. Moreover, decision economists dealing with IBs are usually not willing to invest too much time into study of complex mathematical theories. IB problem is transferred into a decision making tree which indicates all sub-decisions and random lotteries. Random lotteries quantifies such sub-IBs events which are not certain. Such decision trees are evaluated using well known methods. However, the required data sets are often incomplete. The problem of missing data items is solved by introducing a simple and generally applicable heuristic – a longer sequence of events is less probable. A company has legislatively supported several options how to deal with bankruptcy situation. Each of the option can be solved in three different ways by using decision–making tree as tool for probability determination, using already known probabilities from previous case.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

50201 - Economic Theory

Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

6th REDETE Conference RESEARCHING ECONOMIC DEVELOPMENT AND ENTREPRENEURSHIP IN TRANSITION ECONOMIES

ISBN

978-99938-46-80-2

ISSN

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e-ISSN

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Počet stran výsledku

427

Strana od-do

329-345

Název nakladatele

Neuveden

Místo vydání

Banja Luka

Místo konání akce

Banja Luka

Datum konání akce

13. 4. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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