Ontology highlight
ABSTRACT:
SUBMITTER: Lehmann MP
PROVIDER: S-EPMC6897511 | biostudies-literature | 2019 Nov
REPOSITORIES: biostudies-literature
Lehmann Marco P MP Xu He A HA Liakoni Vasiliki V Herzog Michael H MH Gerstner Wulfram W Preuschoff Kerstin K
eLife 20191111
In many daily tasks, we make multiple decisions before reaching a goal. In order to learn such sequences of decisions, a mechanism to link earlier actions to later reward is necessary. Reinforcement learning (RL) theory suggests two classes of algorithms solving this credit assignment problem: In classic temporal-difference learning, earlier actions receive reward information only after multiple repetitions of the task, whereas models with eligibility traces reinforce entire sequences of actions ...[more]