Prospective Optimization.

TitleProspective Optimization.
Publication TypeJournal Article
Year of Publication2014
AuthorsSejnowski TJ, Poizner H, Lynch G, Gepshtein S, Greenspan RJ
JournalProc IEEE Inst Electr Electron Eng
Volume102
Issue5
Date Published2014 May
ISSN0018-9219
Abstract

Human performance approaches that of an ideal observer and optimal actor in some perceptual and motor tasks. These optimal abilities depend on the capacity of the cerebral cortex to store an immense amount of information and to flexibly make rapid decisions. However, behavior only approaches these limits after a long period of learning while the cerebral cortex interacts with the basal ganglia, an ancient part of the vertebrate brain that is responsible for learning sequences of actions directed toward achieving goals. Progress has been made in understanding the algorithms used by the brain during reinforcement learning, which is an online approximation of dynamic programming. Humans also make plans that depend on past experience by simulating different scenarios, which is called prospective optimization. The same brain structures in the cortex and basal ganglia that are active online during optimal behavior are also active offline during prospective optimization. The emergence of general principles and algorithms for goal-directed behavior has consequences for the development of autonomous devices in engineering applications.

DOI10.1109/JPROC.2014.2314297
Alternate JournalProc IEEE Inst Electr Electron Eng
PubMed ID25328167
PubMed Central IDPMC4201124
Grant List / / Howard Hughes Medical Institute / United States
Category: 
Greenspan Laboratory