Definition & Betydelse | Engelska ordet OPTIMALITY

Definition av OPTIMALITY

1. optimalitet

Exempel på hur man kan använda OPTIMALITY i en mening

• The objective is to develop a model or algorithm governing the application of system inputs to drive the system to a desired state, while minimizing any delay, overshoot, or steady-state error and ensuring a level of control stability; often with the aim to achieve a degree of optimality.
• A* (pronounced "A-star") is a graph traversal and pathfinding algorithm that is used in many fields of computer science due to its completeness, optimality, and optimal efficiency.
• That is, they never overestimate the number of moves left, which ensures optimality for certain search algorithms such as A*.
• The gradient methods unique to the MDO community derive from the combination of optimality criteria with math programming, first recognized in the seminal work of Fleury and Schmit who constructed a framework of approximation concepts for structural optimization.
• Using this formulation, we can apply the representer theorem to the RKHS, letting one prove the optimality of using ReLU activations in neural network settings.
• He collaborated with Alfred Aho and Jeffrey Ullman on optimality proofs for paging algorithms, and on a simple proof that compilers based on precedence parsing do not need to backtrack.
• In phylogenetics and computational phylogenetics, maximum parsimony is an optimality criterion under which the phylogenetic tree that minimizes the total number of character-state changes (or minimizes the cost of differentially weighted character-state changes).
• The marginal value theorem (MVT) is an optimality model that usually describes the behavior of an optimally foraging individual in a system where resources (often food) are located in discrete patches separated by areas with no resources.
• Barone, an associate of Pareto, proved an optimality property of perfect competition, namely that – assuming exogenous prices – it maximises the monetary value of the return from productive activity, this being the sum of the values of leisure, savings, and goods for consumption, all taken in the desired proportions.
• Its optimality depends essentially on the use of exact variances and covariances between all measurements and the estimated state and calibration parameters.
• The algorithm's optimality can be improved by using backtracking during the search for the optimal decision tree at the cost of possibly taking longer.
• The idea was to derive a weak variational form of first order necessary conditions for optimality, discretise the time domain in finite intervals and use a simple zero order polynomial representation of states, controls and adjoints over each interval.
• John Staddon conducted theoretical behaviorism research in adaptive function, mechanisms of learning, and optimality theories.
• Thus, from an optimality model it is usually preferable for an organism to inseminate than to be inseminated.
• Seeking optimality, it is a compromise between the competing merits and demerits of the Likert scale and the Analog scale.
• Let x* be a non-degenerate local optimizer of the original problem ("nondegenerate" means that the gradients of the active constraints are linearly independent and the second-order sufficient optimality condition is satisfied).
• This collocation, in conjunction with the proper approximation to the costate, leads to a set of KKT conditions that are identical to the discretized form of the first-order optimality conditions.
• In addition to introducing RRTs, he coined the term "sampling-based motion planning" and developed numerous planning algorithms for handling typical control-theoretic problems such as kinematic constraints, momentum, feedback, multiobjective optimality, and stochastic uncertainty.
• Proponents of generalized game theory have advocated the application of the theory to reconceptualizing individual and collective decision-making, resolutions of the prisoners' dilemma game, agent-based modeling, fuzzy games, conflict resolution procedures, challenging and providing robust and normatively grounded alternatives to Nash equilibrium and Pareto optimality, among others.
• Gallager in 1968 along with the water-pouring theorem which proves its optimality for channels having Additive White Gaussian Noise (AWGN) and intersymbol interference (ISI).

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