Sample-efficiency in multi-batch reinforcement learning: the need for dimension-dependent adaptivity

We theoretically explore the relationship between sample-efficiency and adaptivity in reinforcement learning. An algorithm is sample-efficient if it uses a number of queries n to the environment that is polynomial in the dimension d of the problem. Adaptivity refers to the frequency at which queries...

Szczegółowa specyfikacja

Opis bibliograficzny
Główni autorzy: Johnson, E, Pike-Burke, C, Rebeschini, P
Format: Conference item
Język:English
Wydane: OpenReview 2024