Highlights & Insights Theory-Practice Unification: BLAE is the first batched linear bandit algorithm that achieves both minimax optimal regret (in both regimes) and outstanding practical performance, ...

Abstract: In the cooperative multi-armed bandits problem, multiple agents cooperatively play the same multi-armed bandit game. The goal is to develop bandit algorithms with optimal group and ...

Abstract: This article considers the problem of efficient sampling for toxicity detection in competitive online video games. Video game service operators take proactive measures to detect and address ...

Ashely Claudino is an Evergreen Staff Writer from Portugal. She has a Translation degree from the University of Lisbon (2020, Faculty of Arts and Humanities). She has been writing for Game Rant since ...

We study a contextual bandit setting where the agent has access to causal side information, in addition to the ability to perform multiple targeted experiments corresponding to potentially different ...

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Vector norms play a fundamental role in computer science and optimization, so there is an ongoing effort to generalize existing algorithms to settings beyond ℓ∞ and ℓp norms. We show that many online ...

Scientists have introduced a photonic reinforcement learning scheme, progressing from the static multi-armed bandit problem to a dynamic environment, using quantum interference of photons to enhance ...