  The freshness or timeliness of data at server is a significant key
performance indicator of sensor networks, especially in tolerance critical
applications such as factory automation. As an effective and intuitive
measurement to data timeliness, the metric of Age of Information (AoI) has
attracted an intensive recent interest of research. This paper initiates a
study on the AoI of wireless sensor networks working in the finite blocklength
(FBL) regime as a resource allocation problem, and proposes to minimize the
long-term discounted system AoI as a Markov decision process (MDP). The
proposed method with its optimum solved by Reinforced Learning technique is
verified by simulations to outperform benchmarks, including the conventional
error rate minimizing policy.
