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In behavioral economics, time preference (or time discounting, [1] delay discounting, temporal discounting, [2] long-term orientation [3]) is the current relative valuation placed on receiving a good at an earlier date compared with receiving it at a later date. [1] Applications for these preferences include finance, health, climate change.
An abstract, high-level construal of an activity (e.g., "learning to speak French") may lead to a more positive evaluation of that activity than a concrete, low-level construal (e.g., "learning to conjugate the irregular French verb 'avoir ' "). Thus, CLT predicts that we will think about the value of the low-level construals when evaluating an ...
Hyperbolic discounting is mathematically described as = + where g(D) is the discount factor that multiplies the value of the reward, D is the delay in the reward, and k is a parameter governing the degree of discounting (for example, the interest rate).
In findings presented in the journal Proceedings of the Royal Society B in 2021, Marine Biological Laboratory, researchers described cuttlefish (Sepia officinalis) that were able to pass an adapted version of the marshmallow test. Cephalopods engage in "future-oriented foraging" and the nine-month-old cuttlefish in the experiments were able to ...
Exponential discounting yields time-consistent preferences. Exponential discounting and, more generally, time-consistent preferences are often assumed in rational choice theory, since they imply that all of a decision-maker's selves will agree with the choices made by each self. Any decision that the individual makes for himself in advance will ...
Hyperbolic discounting, where discounting is the tendency for people to have a stronger preference for more immediate payoffs relative to later payoffs. Hyperbolic discounting leads to choices that are inconsistent over time—people make choices today that their future selves would prefer not to have made, despite using the same reasoning. [52]
In economics, a discount function is used in economic models to describe the weights placed on rewards received at different points in time. For example, if time is discrete and utility is time-separable, with the discount function f(t) having a negative first derivative and with c t (or c(t) in continuous time) defined as consumption at time t, total utility from an infinite stream of ...
Preference learning is a subfield of machine learning that focuses on modeling and predicting preferences based on observed preference information. [1] Preference learning typically involves supervised learning using datasets of pairwise preference comparisons, rankings, or other preference information.