3 Result(s)
-
Chapter and Conference Paper
Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees
Deep Reinforcement Learning (DRL) has achieved impressive success in many applications. A key component of many DRL models is a neural network representing a Q function, to estimate the expected cumulative rew...
-
Chapter and Conference Paper
Interpreting Deep Sports Analytics: Valuing Actions and Players in the NHL
Deep learning has started to have an impact on sports analytics. Several papers have applied action-value Q learning to quantify a team’s chance of success, given the current match state. However, the black-bo...
-
Article
Deep soccer analytics: learning an action-value function for evaluating soccer players
Given the large pitch, numerous players, limited player turnovers, and sparse scoring, soccer is arguably the most challenging to analyze of all the major team sports. In this work, we develop a new approach t...
