Decision Making & Mathematical Modeling

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Decision Making & Mathematical Modeling

Introduction to Decision Making & Mathematical Modeling

The goal of this Decision Making & Mathematical Modeling is to build an automaton that represents the basic characteristics of human behavior in the decision-making process.

Defined Mathematical Models

Real-world situations can be represented mathematically. Indeed, mathematical models are the tools employed to portray the real world in mathematical terms. They assist us in comprehending how the real world operates.

Most models do not precisely reproduce the real world, but rather provide a simplified representation of real-life circumstances.

Defined Decision Making

Making choices is an essential action in business. It frequently includes several people with opposing viewpoints. Decision-making mathematical models can be quite useful in this situation. Such models employ input data and a set of conditions that must be met to assist management in making a decision.

The investment choice is one of the most typical decision-making challenges that every business has, since it must determine whether or not to spend its money in a project. For making such judgments, businesses frequently employ mathematical models that compare the prospective valuation of the project to the investment to be made.

What is mathematical modelling?

Models describe our beliefs about how the world functions. In mathematical modelling, we translate those beliefs into the language of mathematics. This has many advantages

  1. Mathematics is a very precise language. This helps us to formulate ideas and identify underlying assumptions.
  2. Mathematics is a concise language, with well-defined rules for manipulations.
  3. All the results that mathematicians have proved over hundreds of years are at our disposal.
  4. Computers can be used to perform numerical calculations.

    What objectives can modelling achieve?

    Mathematical modelling can be used for several different reasons. How well any particular

    objective is achieved depends on both the state of knowledge about a system and how well the

    modelling is done. Examples of the range of objectives are:

    1. Developing scientific understanding- through the quantitative expression of current knowledge of a system (as well as displaying what we know, this may also show up what we do not know);
    2. test the effect of changes in a system;
    3. aid decision making, including
    4. tactical decisions by managers;
    5. strategic decisions by planners.

    Decision model

    The decision model is very useful in the field of cognitive psychology. It has been observed that decision corresponds to the acquisition, and the processing of information allows people to choose between several options and, therefore, act based on a decision. This process is fundamental and consists of six stages consecutive. These stages are, represented by two models: personalization and transitory state

     

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