Decision Model
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Decision Model
A decision model in decision theory is the starting point for a decision method within a formal (axiomatic) system. Decision models contain at least one action axiom. An action is in the form "IF is true, THEN do ". An action axiom tests a condition (antecedent) and, if the condition has been met, then (consequent) it suggests (mandates) an action: from knowledge to action. A decision model may also be a network of connected decisions, information and knowledge that represents a decision-making approach that can be used repeatedly (such as one developed using the Decision Model and Notation standard). Excepting very simple situations, successful action axioms are used in an iterative manner. For example, for decision analysis, the sole action axiom occurs in the Evaluation stage of a four-step cycle: Formulate, Evaluate, Interpret/Appraise, Refine. Decision models are used both to model a decision being made once, as well as to model a repeatable decision-making approach that wi ...
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Decision Theory
Decision theory (or the theory of choice; not to be confused with choice theory) is a branch of applied probability theory concerned with the theory of making decisions based on assigning probabilities to various factors and assigning numerical consequences to the outcome. There are three branches of decision theory: # Normative decision theory: Concerned with the identification of optimal decisions, where optimality is often determined by considering an ideal decision-maker who is able to calculate with perfect accuracy and is in some sense fully rational. # Prescriptive decision theory: Concerned with describing observed behaviors through the use of conceptual models, under the assumption that those making the decisions are behaving under some consistent rules. # Descriptive decision theory: Analyzes how individuals actually make the decisions that they do. Decision theory is closely related to the field of game theory and is an interdisciplinary topic, studied by econom ...
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Algorithm
In mathematics and computer science, an algorithm () is a finite sequence of rigorous instructions, typically used to solve a class of specific Computational problem, problems or to perform a computation. Algorithms are used as specifications for performing calculations and data processing. More advanced algorithms can perform automated deductions (referred to as automated reasoning) and use mathematical and logical tests to divert the code execution through various routes (referred to as automated decision-making). Using human characteristics as descriptors of machines in metaphorical ways was already practiced by Alan Turing with terms such as "memory", "search" and "stimulus". In contrast, a Heuristic (computer science), heuristic is an approach to problem solving that may not be fully specified or may not guarantee correct or optimal results, especially in problem domains where there is no well-defined correct or optimal result. As an effective method, an algorithm ca ...
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Decision Support
A decision support system (DSS) is an information system that supports business or organizational decision-making activities. DSSs serve the management, operations and planning levels of an organization (usually mid and higher management) and help people make decisions about problems that may be rapidly changing and not easily specified in advanceā€”i.e. unstructured and semi-structured decision problems. Decision support systems can be either fully computerized or human-powered, or a combination of both. While academics have perceived DSS as a tool to support decision making processes, DSS users see DSS as a tool to facilitate organizational processes. Some authors have extended the definition of DSS to include any system that might support decision making and some DSS include a decision-making software component; Sprague (1980)Sprague, R;(1980).A Framework for the Development of Decision Support Systems" MIS Quarterly. Vol. 4, No. 4, pp.1-25. defines a properly termed DSS a ...
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Decision-making Models
Decision-making as a team is a scientific process when that decision will affect a policy affecting an entity. Decision-making models are used as a method and process to fulfill the following objectives: * Every team member is clear about how a decision will be made * The roles and responsibilities for the decision making * Who will own the process to make the final decision These models help the team to plan the process and the agenda for each decision-making meeting, and the understanding of the process and collaborative approach helps in achieving the support of the team members for the final decision to ensure commitment for the same. Types There are several models of decision-making: Economic rationality model When using this model, the following conditions are assumed. # The decision will be completely rational in a means-ends sense. # There is a complete and consistent system of preferences that allows a choice among alternatives. # There is a complete awareness of all ...
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Decision Engineering
Decision intelligence is an engineering discipline that augments data science with theory from social science, decision theory, and managerial science. Its application provides a framework for best practices in organizational decision-making and processes for applying machine learning at scale. The basic idea is that decisions are based on our understanding of how actions lead to outcomes. Decision intelligence is a discipline for analyzing this chain of cause and effect, and decision modeling is a visual language for representing these chains. A related field decision engineering also investigates the improvement of decision-making processes but is not always as closely tied to data science. Origins and technologies Decision intelligence is based on the recognition that, in many organizations, decision-making could be improved if a more structured approach were used. Decision intelligence seeks to overcome a decision-making "complexity ceiling", which is characterized by a mis ...
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Value Of Revelation
Value or values may refer to: Ethics and social * Value (ethics) wherein said concept may be construed as treating actions themselves as abstract objects, associating value to them ** Values (Western philosophy) expands the notion of value beyond that of ethics, but limited to Western sources * Social imaginary is the set of values, institutions, laws, and symbols common to a particular social group Economics * Value (economics), a measure of the benefit that may be gained from goods or service ** Theory of value (economics), the study of the concept of economic value ** Value (marketing), the difference between a customer's evaluation of benefits and costs ** Value investing, an investment paradigm * Values (heritage), the measure by which the cultural significance of heritage items is assessed * Present value * Present value of benefits Business * Business value * Customer value proposition * Employee value proposition * Value (marketing) * Value proposition Other uses ...
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Value Of Prediction
Value or values may refer to: Ethics and social * Value (ethics) wherein said concept may be construed as treating actions themselves as abstract objects, associating value to them ** Values (Western philosophy) expands the notion of value beyond that of ethics, but limited to Western sources * Social imaginary is the set of values, institutions, laws, and symbols common to a particular social group Economics * Value (economics), a measure of the benefit that may be gained from goods or service ** Theory of value (economics), the study of the concept of economic value ** Value (marketing), the difference between a customer's evaluation of benefits and costs ** Value investing, an investment paradigm * Values (heritage), the measure by which the cultural significance of heritage items is assessed * Present value * Present value of benefits Business * Business value * Customer value proposition * Employee value proposition * Value (marketing) * Value proposition Other uses ...
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Sensitivity Analysis
Sensitivity analysis is the study of how the uncertainty in the output of a mathematical model or system (numerical or otherwise) can be divided and allocated to different sources of uncertainty in its inputs. A related practice is uncertainty analysis, which has a greater focus on uncertainty quantification and propagation of uncertainty; ideally, uncertainty and sensitivity analysis should be run in tandem. The process of recalculating outcomes under alternative assumptions to determine the impact of a variable under sensitivity analysis can be useful for a range of purposes, including: * Testing the robustness of the results of a model or system in the presence of uncertainty. * Increased understanding of the relationships between input and output variables in a system or model. * Uncertainty reduction, through the identification of model input that cause significant uncertainty in the output and should therefore be the focus of attention in order to increase robustness (perhap ...
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Evaluation
Evaluation is a systematic determination and assessment of a subject's merit, worth and significance, using criteria governed by a set of standards. It can assist an organization, program, design, project or any other intervention or initiative to assess any aim, realisable concept/proposal, or any alternative, to help in decision-making; or to ascertain the degree of achievement or value in regard to the aim and objectives and results of any such action that has been completed. The primary purpose of evaluation, in addition to gaining insight into prior or existing initiatives, is to enable reflection and assist in the identification of future change. Evaluation is often used to characterize and appraise subjects of interest in a wide range of human enterprises, including the arts, criminal justice, foundations, non-profit organizations, government, health care, and other human services. It is long term and done at the end of a period of time. Definition Evaluation is the st ...
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Decision Making
In psychology, decision-making (also spelled decision making and decisionmaking) is regarded as the cognitive process resulting in the selection of a belief or a course of action among several possible alternative options. It could be either rational or irrational. The decision-making process is a reasoning process based on assumptions of values, preferences and beliefs of the decision-maker. Every decision-making process produces a final choice, which may or may not prompt action. Research about decision-making is also published under the label problem solving, particularly in European psychological research. Overview Decision-making can be regarded as a problem-solving activity yielding a solution deemed to be optimal, or at least satisfactory. It is therefore a process which can be more or less rational or irrational and can be based on explicit or tacit knowledge and beliefs. Tacit knowledge is often used to fill the gaps in complex decision-making processes. Usually, both o ...
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Business Rules
A business rule defines or constrains some aspect of business. It may be expressed to specify an action to be taken when certain conditions are true or may be phrased so it can only resolve to either true or false. Business rules are intended to assert business structure or to control or influence the behavior of the business. Business rules describe the operations, definitions and constraints that apply to an organization. Business rules can apply to people, processes, corporate behavior and computing systems in an organization, and are put in place to help the organization achieve its goals. For example, a business rule might state that ''no credit check is to be performed on return customers''. Other examples of business rules include requiring a rental agent to disallow a rental tenant if their credit rating is too low, or requiring company agents to use a list of preferred suppliers and supply schedules. While a business rule may be informal or even unwritten, documenting the ...
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Decision Tree
A decision tree is a decision support tool that uses a tree-like model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. It is one way to display an algorithm that only contains conditional control statements. Decision trees are commonly used in operations research, specifically in decision analysis, to help identify a strategy most likely to reach a goal, but are also a popular tool in machine learning. Overview A decision tree is a flowchart-like structure in which each internal node represents a "test" on an attribute (e.g. whether a coin flip comes up heads or tails), each branch represents the outcome of the test, and each leaf node represents a class label (decision taken after computing all attributes). The paths from root to leaf represent classification rules. In decision analysis, a decision tree and the closely related influence diagram are used as a visual and analytical decision support tool, where t ...
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