Khái niệm cốt lõi
The core message of this paper is to propose a principled policy learning approach that effectively balances the short-term and long-term rewards, addressing the challenges of confounding bias and missing long-term outcomes.
Tóm tắt
The paper presents a new framework for learning the optimal policy that balances both long-term and short-term rewards, where some long-term outcomes are allowed to be missing. The authors first introduce identifiability assumptions to address the confounding bias and missing data issues. They then derive the efficient influence functions and semiparametric efficiency bounds for estimating the short-term and long-term rewards. Based on these results, the authors develop novel estimators that are consistent, asymptotically normal, and semiparametric efficient. They further reveal that short-term outcomes, if associated, can contribute to improving the estimator of the long-term reward. Finally, the authors learn the optimal policy by solving an optimization problem that balances the estimated short-term and long-term rewards, and provide convergence rate analysis for the regret and estimation error of the learned policy.
The key highlights and insights are:
Formulation of a new policy learning setting that aims to balance short-term and long-term rewards.
Introduction of identifiability assumptions to address confounding bias and missing long-term outcomes.
Derivation of efficient influence functions and semiparametric efficiency bounds for estimating short-term and long-term rewards.
Development of novel estimators that are consistent, asymptotically normal, and semiparametric efficient.
Revelation that short-term outcomes can contribute to improving the estimator of long-term rewards.
Learning of the optimal policy by solving an optimization problem that balances short-term and long-term rewards.
Convergence rate analysis for the regret and estimation error of the learned policy.
Extensive experiments demonstrating the effectiveness of the proposed approach.
Thống kê
The paper does not provide any specific data or statistics. It focuses on the theoretical development of the policy learning framework.
Trích dẫn
"While the significance of long-term outcomes is undeniable, an overemphasis on them may inadvertently overshadow short-term gains."
"Long-term effects can significantly differ from short-term effects, and in some cases, they may even exhibit opposing trends."