https://www.selleckchem.com/pr....oducts/atuveciclib-b
Finally, we also explain on randomly chosen examples how the classifier takes decisions.This brief proposes a game-theoretic inverse reinforcement learning (GT-IRL) framework, which aims to learn the parameters in both the dynamic system and individual cost function of multistage games from demonstrated trajectories. Different from the probabilistic approaches in computer science community and residual minimization solutions in control community, our framework addresses the problem in a deterministic setting by different