The time average expected age of information (AoI) is studied for status updates sent over an error-prone channel from an energy-harvesting transmitter with a finite-capacity battery. Energy cost of sensing new status updates is taken into account as well as the transmission energy cost better capturing practical systems. The optimal scheduling policy is first studied under the hybrid automatic repeat request (HARQ) protocol when the channel and energy harvesting statistics are known, and the existence of a threshold-based optimal policy is shown. For the case of unknown environments, average-cost reinforcement-learning algorithms are proposed that learn the system parameters and the status update policy in real-time. The effectiveness of the proposed methods is demonstrated through numerical results.

翻译：研究信息的平均预期年龄(AoI),以便从一个具有有限容量电池的能源收获发射机中通过一个容易出错的频道发送最新信息; 将遥感新状态更新的能源成本以及传输能源成本更好地捕捉实用系统的能源成本考虑在内; 在了解频道和能源收获统计数据时,首先根据混合自动重复请求(HARQ)协议研究最佳时间安排政策,并显示存在基于门槛的最佳政策; 对于未知环境的情况,建议采用平均成本强化学习算法,实时学习系统参数和状况更新政策; 通过数字结果显示拟议方法的有效性。