SimulationA simulation is the imitation of the operation of a real-world process or system over time. Simulations require the use of models; the model represents the key characteristics or behaviors of the selected system or process, whereas the simulation represents the evolution of the model over time. Often, computers are used to execute the simulation. Simulation is used in many contexts, such as simulation of technology for performance tuning or optimizing, safety engineering, testing, training, education, and video games.
Decision-makingIn 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.
Measurement uncertaintyIn metrology, measurement uncertainty is the expression of the statistical dispersion of the values attributed to a measured quantity. All measurements are subject to uncertainty and a measurement result is complete only when it is accompanied by a statement of the associated uncertainty, such as the standard deviation. By international agreement, this uncertainty has a probabilistic basis and reflects incomplete knowledge of the quantity value. It is a non-negative parameter.
Simulation hypothesisThe simulation hypothesis proposes that all of existence is a simulated reality, such as a computer simulation. This simulation could contain conscious minds that may or may not know that they live inside a simulation. This is quite different from the current, technologically achievable concept of virtual reality, which is easily distinguished from the experience of actuality. Simulated reality, by contrast, would be hard or impossible to separate from "true" reality.
Uncertainty quantificationUncertainty quantification (UQ) is the science of quantitative characterization and estimation of uncertainties in both computational and real world applications. It tries to determine how likely certain outcomes are if some aspects of the system are not exactly known. An example would be to predict the acceleration of a human body in a head-on crash with another car: even if the speed was exactly known, small differences in the manufacturing of individual cars, how tightly every bolt has been tightened, etc.
Computer simulationComputer simulation is the process of mathematical modelling, performed on a computer, which is designed to predict the behaviour of, or the outcome of, a real-world or physical system. The reliability of some mathematical models can be determined by comparing their results to the real-world outcomes they aim to predict. Computer simulations have become a useful tool for the mathematical modeling of many natural systems in physics (computational physics), astrophysics, climatology, chemistry, biology and manufacturing, as well as human systems in economics, psychology, social science, health care and engineering.
Decision-making softwareDecision-making software (DM software) is software for computer applications that help individuals and organisations make choices and take decisions, typically by ranking, prioritizing or choosing from a number of options. An early example of DM software was described in 1973. Before the advent of the World Wide Web, most DM software was spreadsheet-based, with the first web-based DM software appearing in the mid-1990s. Nowadays, many DM software products (mostly web-based) are available – e.g.
Propagation of uncertaintyIn statistics, propagation of uncertainty (or propagation of error) is the effect of variables' uncertainties (or errors, more specifically random errors) on the uncertainty of a function based on them. When the variables are the values of experimental measurements they have uncertainties due to measurement limitations (e.g., instrument precision) which propagate due to the combination of variables in the function. The uncertainty u can be expressed in a number of ways. It may be defined by the absolute error Δx.
Group decision-makingGroup decision-making (also known as collaborative decision-making or collective decision-making) is a situation faced when individuals collectively make a choice from the alternatives before them. The decision is then no longer attributable to any single individual who is a member of the group. This is because all the individuals and social group processes such as social influence contribute to the outcome. The decisions made by groups are often different from those made by individuals.
Consensus decision-makingConsensus decision-making or consensus process (often abbreviated to consensus) are group decision-making processes in which participants develop and decide on proposals with the aim, or requirement, of acceptance by all. The focus on establishing agreement of at least the majority or the supermajority and avoiding unproductive opinion differentiates consensus from unanimity, which requires all participants to support a decision. The word consensus is Latin meaning "agreement, accord", derived from consentire meaning "feel together".
Vehicle simulation gameVehicle simulation games are a genre of video games which attempt to provide the player with a realistic interpretation of operating various kinds of vehicles. This includes automobiles, aircraft, watercraft, spacecraft, military vehicles, and a variety of other vehicles. The main challenge is to master driving and steering the vehicle from the perspective of the pilot or driver, with most games adding another challenge such as racing or fighting rival vehicles.
Automated decision-makingAutomated decision-making (ADM) involves the use of data, machines and algorithms to make decisions in a range of contexts, including public administration, business, health, education, law, employment, transport, media and entertainment, with varying degrees of human oversight or intervention. ADM involves large-scale data from a range of sources, such as databases, text, social media, sensors, images or speech, that is processed using various technologies including computer software, algorithms, machine learning, natural language processing, artificial intelligence, augmented intelligence and robotics.
Stochastic processIn probability theory and related fields, a stochastic (stəˈkæstɪk) or random process is a mathematical object usually defined as a sequence of random variables, where the index of the sequence has the interpretation of time. Stochastic processes are widely used as mathematical models of systems and phenomena that appear to vary in a random manner. Examples include the growth of a bacterial population, an electrical current fluctuating due to thermal noise, or the movement of a gas molecule.
Poisson point processIn probability, statistics and related fields, a Poisson point process is a type of random mathematical object that consists of points randomly located on a mathematical space with the essential feature that the points occur independently of one another. The Poisson point process is often called simply the Poisson process, but it is also called a Poisson random measure, Poisson random point field or Poisson point field.
Object-oriented programmingObject-Oriented Programming (OOP) is a programming paradigm based on the concept of "objects", which can contain data and code. The data is in the form of fields (often known as attributes or properties), and the code is in the form of procedures (often known as methods). A common feature of objects is that procedures (or methods) are attached to them and can access and modify the object's data fields. In this brand of OOP, there is usually a special name such as or used to refer to the current object.
Object lifetimeIn object-oriented programming (OOP), the object lifetime (or life cycle) of an object is the time between an object's creation and its destruction. Rules for object lifetime vary significantly between languages, in some cases between implementations of a given language, and lifetime of a particular object may vary from one run of the program to another. In some cases, object lifetime coincides with variable lifetime of a variable with that object as value (both for static variables and automatic variables), but in general, object lifetime is not tied to the lifetime of any one variable.
Object modelIn computing, object model has two related but distinct meanings: The properties of objects in general in a specific computer programming language, technology, notation or methodology that uses them. Examples are the object models of Java, the Component Object Model (COM), or Object-Modeling Technique (OMT). Such object models are usually defined using concepts such as class, generic function, message, inheritance, polymorphism, and encapsulation.
Object (computer science)In computer science, an object can be a variable, a data structure, a function, or a method. As regions of memory, objects contain a value and are referenced by identifiers. In the object-oriented programming paradigm, an object can be a combination of variables, functions, and data structures; in particular in class-based variations of the paradigm, an object refers to a particular instance of a class. In the relational model of database management, an object can be a table or column, or an association between data and a database entity (such as relating a person's age to a specific person).
