We present a co-design method for wireless networked control systems (WNCS) that optimizes both the network and control parameters for optimal performance. The objective is to make the system resource-efficient by introducing the possibility of switching the control policy from reliable control to energy-efficient control, or by optimizing the power consumption using variable inter-packet gap (IPG) in the wireless communication layer. An RL-based approach is used to ensure efficient resource allocation and create effective control performance under moderate to high packet loss. This is achieved by formulating a multi-objective problem that considers both resource efficiency and reliability. Subsequently, the proposed algorithm is used to solve this multi-objective problem. Simulation results show that despite situations where the network experiences packet losses, the proposed co-design reinforcement learning (RL)-based control technique effectively maintains, or in some cases even improves control performance. In contrast to conventional control, where a 15% packet loss in the network causes control performance to completely fail (unstable behavior), the proposed RL-based approach is immune to network packet loss (acceptable performance, i.e., control stability until 30% of packet loss) and also demonstrates the capability to achieve an average reduction in transmission power of up-to 10%.