13 citations · 25 across the 5 of their papers we have counts for
5 papers
Self-Play PSRO: Toward Optimal Populations in Two-Player Zero-Sum Games
Stephen McAleer, JB Lanier, Kevin Wang +3
In competitive two-agent environments, deep reinforcement learning (RL) methods based on the \emph{Double Oracle (DO)} algorithm, such as \emph{Policy Space Response Oracles (PSRO)…
Feasible Adversarial Robust Reinforcement Learning for Underspecified Environments
JB Lanier, Stephen McAleer, Pierre Baldi +1
Robust reinforcement learning (RL) considers the problem of learning policies that perform well in the worst case among a set of possible environment parameter values. In real-worl…
Target Entropy Annealing for Discrete Soft Actor-Critic
Yaosheng Xu, Dailin Hu, Litian Liang +3
Soft Actor-Critic (SAC) is considered the state-of-the-art algorithm in continuous action space settings. It uses the maximum entropy framework for efficiency and stability, and ap…
Measuring the Polarization Reconstruction Resolution of the ARIANNA Neutrino Detector with Cosmic Rays
ARIANNA Collaboration, A. Anker, P. Baldi +30
The ARIANNA detector is designed to detect neutrinos with energies above eV. Due to the similarities in generated radio signals, cosmic rays are often used as test beams f…
Improving sensitivity of the ARIANNA detector by rejecting thermal noise with deep learning
ARIANNA Collaboration, A. Anker, P. Baldi +30
The ARIANNA experiment is an Askaryan detector designed to record radio signals induced by neutrino interactions in the Antarctic ice. Because of the low neutrino flux at high ener…