激励学习的最优判据研究

激励学习智能体通过最优策略的学习与规划来求解序贯决策问题，因此如何定义策略的最优判所是激励学习研究的核心问题之一，本文讨论了一系列来自动态规划的最优判据，通过实例检验了各种判据对激励学习的适用性和优缺点，分析了设计各种判据的激励学习算法的必要性。

Research on Optimality Criteria in Reinforcement Learning

RL agents solve sequential decision problems by learning optim policies for choosing actions.Thus,at the core of RL is the definition of what it means for a policy to be “optimal”.In this paper,a variety of optimality criteria from the dynamic programming literature are discussed,and their suitability and characteristics for RL is examined through s ome examples.The necessity of devising RL algorithms for the various criteria has also been analyzed.