2010/01/25 by William H. Alexander, Joshua W. Brown · 1 citation
Decision Sciences · Neuroscience · Psychology · #Decision-Making and Behavioral Economics #Neural and Behavioral Psychology Studies #Child and Animal Learning Development
paper · doi:10.1162/neco.2010.08-09-1080
openalex publication_date 2010/01/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/10
Hyperbolic discounting of future outcomes is widely observed to underlie choice behavior in animals. Additionally, recent studies (Kobayashi & Schultz, 2008) have reported that hyperbolic discounting is observed even in neural systems underlying choice. However, the most prevalent models of temporal discounting, such as temporal difference learning, assume that future outcomes are discounted exponentially. Exponential discounting has been preferred largely because it can be expressed recursively, whereas hyperbolic discounting has heretofore been thought not to have a recursive definition. In this letter, we define a learning algorithm, hyperbolically discounted temporal difference (HDTD) learning, which constitutes a recursive formulation of the hyperbolic model.