Universal Knowledge-Seeking Agents for Stochastic Environments

Date

Authors

Orseau, Laurent
Lattimore, Tor
Hutter, Marcus

Journal Title

Journal ISSN

Volume Title

Publisher

Landes Bioscience/Springer Science+Business Media

Abstract

We define an optimal Bayesian knowledge-seeking agent, KL-KSA, designed for countable hypothesis classes of stochastic environments and whose goal is to gather as much information about the unknown world as possible. Although this agent works for arbitrar

Description

Keywords

Citation

Source

Lecture Notes in Artificial Intelligence

Book Title

Entity type

Access Statement

Open Access

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Restricted until