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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.
Time discounting or temporal discounting is a wide range of ideas involving the connection between time and the extent to which an object, situation, or course of action is seen as valuable. The overall theory is that people put more value and worth into immediate events and outcomes, and apply less value to future outcomes or events.
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 real world situations, "discounting makes sense because of the inherent uncertainty of future payoffs". [55] One study looked at how reward discounting is context specific. [18] By differing the time and space between small and large rewards, they were able to test how these factors affected the decision making in tamarins and marmosets ...
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 ...
The term of present bias was coined in the second half of the 20th century. In the 1930s economic research started investigating time preferences. The findings led to the model of exponential discounting, thus time consistent discounting. However, later research led to the conclusion that time preferences were indeed not consistent, but ...
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.