Prospective Optimization

Bibliographic Collection: 
CARTA-Inspired Publication
Publication Type: Journal Article
Authors: Sejnowski, TJ; Poizner, H; Lynch, G; Gepshtein, S; Greenspan, R
Year of Publication: 2014
Journal: Proc IEEE Inst Electr Electron Eng
Volume: 102
Issue: 5
Date Published: 05/2014
Publication Language: eng
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.

DOI: 10.1109/JPROC.2014.2314297
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