Provably Efficient Interactive-Grounded Learning with Personalized
Reward
Provably Efficient Interactive-Grounded Learning with Personalized
Reward
Interactive-Grounded Learning (IGL) [Xie et al., 2021] is a powerful framework in which a learner aims at maximizing unobservable rewards through interacting with an environment and observing reward-dependent feedback on the taken actions. To deal with personalized rewards that are ubiquitous in applications such as recommendation systems, Maghakian et al. …