In biology, optimality models are a tool used to evaluate the costs and benefits of different organismal features, traits, and characteristics, including behavior, in the natural world. This evaluation allows researchers to make predictions about an organism's optimal behavior or other aspects of its phenotype. Optimality modeling is the modeling aspect of optimization theory. It allows for the calculation and visualization of the costs and benefits that influence the outcome of a decision, and contributes to an understanding of adaptations. The approach based on optimality models in biology is sometimes called optimality theory.[1]
Optimal behavior is defined as an action that maximizes the difference between the costs and benefits of that decision. Three primary variables are used in optimality models of behavior: decisions, currency, and constraints.[2] Decision involves evolutionary considerations of the costs and benefits of their actions. Currency is defined as the variable that is intended to be maximized (ex. food per unit of energy expenditure). It is the driving factor behind an action and usually involves food or other items essential to an organism's survival. Constraints refer to the limitations placed on behavior, such as time and energy used to conduct that behavior, or possibly limitations inherent to their sensory abilities.
Optimality models are used to predict optimal behavior (ex. time spent foraging). To make predictions about optimal behavior, cost-benefit graphs are used to visualize the optimality model (see Fig 1). Optimality occurs at the point in which the difference between benefits and costs for obtaining a currency via a particular behavior is maximized.
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^Lucas, Jeffrey R. (August 1983). "The Role of Foraging Time Constraints and Variable Prey Encounter in Optimal Diet Choice". The American Naturalist. 122 (2): 191–209. doi:10.1086/284130. S2CID 85216873.
predictions about an organism's optimal behavior or other aspects of its phenotype. Optimalitymodeling is the modeling aspect of optimization theory....
constructing approximately optimal designs, depending on the model specified and the optimality criterion. Users may use a standard optimality-criterion or may...
use to achieve this goal. OFT is an ecological application of the optimalitymodel. This theory assumes that the most economically advantageous foraging...
The marginal value theorem (MVT) is an optimalitymodel that usually describes the behavior of an optimally foraging individual in a system where resources...
linguistics, optimality theory (frequently abbreviated OT) is a linguistic model proposing that the observed forms of language arise from the optimal satisfaction...
smaller subproblems. Bellman's principle of optimality describes how to do this: Principle of Optimality: An optimal policy has the property that whatever the...
statistics, an optimality criterion provides a measure of the fit of the data to a given hypothesis, to aid in model selection. A model is designated as...
Bateman's principle, almost always burdens the "mother". Thus, from an optimalitymodel it is usually preferable for an organism to inseminate than to be inseminated...
Hyperparameter optimization finds a tuple of hyperparameters that yields an optimalmodel which minimizes a predefined loss function on given independent data...
better results than the average of all the individual models. It can also be proved that if the optimal weighting scheme is used, then a weighted averaging...
policy is still optimal with quantity discounts. Perera et al. (2017) establish this optimality and fully characterize the (s,S) optimality within the EOQ...
the physical system: it is the solution of the mathematical model's equation. In optimal control theory, these equations are referred to as the state...
Behavioral ecologists use economic models and categories to understand foraging; many of these models are a type of optimalmodel. Thus foraging theory is discussed...
probability on the x-axis. ROC analysis provides tools to select possibly optimalmodels and to discard suboptimal ones independently from (and prior to specifying)...
In finance, the Markowitz model ─ put forward by Harry Markowitz in 1952 ─ is a portfolio optimization model; it assists in the selection of the most efficient...
certain optimality criterion is achieved. A control problem includes a cost functional that is a function of state and control variables. An optimal control...
nonsatiation to get to a weak Pareto optimum. Constrained Pareto efficiency is a weakening of Pareto optimality, accounting for the fact that a potential...
model structure with optimal complexity indicated by the minimum value of an external criterion. This process is called self-organization of models....
sequential design, optimal experimental design (OED) or active learning) Construction of the surrogate model and optimizing the model parameters (i.e.,...
an optimum currency area, and provides a comparative before-and-after model by which to test the principles of the theory. In theory, an optimal currency...
construction of the optimalmodel. In the early 1980s Ivakhnenko had established an organic analogy between the problem of constructing models for noisy data...
A large language model (LLM) is a computational model notable for its ability to achieve general-purpose language generation and other natural language...
practical point of view and on a theoretical one, since the existence of an optimalmodel and the consistency of the empirical risk minimization can be proved...
Christopher V.; Scokaert, Pierre O. M. (2000). "Constrained model predictive control: stability and optimality". Automatica. 36 (6): 789–814. doi:10.1016/S0005-1098(99)00214-9...
sufficient to establish at least local optimality. The envelope theorem describes how the value of an optimal solution changes when an underlying parameter...
diffusion models, also known as diffusion probabilistic models or score-based generative models, are a class of latent variable generative models. A diffusion...
"current" [on-policy] or the optimal [off-policy] one). These methods rely on the theory of Markov decision processes, where optimality is defined in a sense...
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