The acoustic liner is an important technology to reduce noise transmission in ducts, for applications ranging from heating and air-conditioning ventilation systems, to aircraft turbofan engines. In particular, the new generation of Ultra-High-By-Pass-Ratio turbofan engine while reducing fuel consumption, threatens higher noise levels at low frequencies because of its larger diameter, lower number of blades and rotational speed. Moreover, this is accompanied by a shorter nacelle, leaving less available space for acoustic treatments. This need of higher performances, has encouraged research in the field of innovative acoustic liners. In this paper, we review some guidelines generally employed for the design of acoustic liners, along with their substantial limitations. Then, the state of art of the research in innovative liners is presented, including both passive and active solutions. This work defines the background for our following quest towards the employment of reinforcement-learning algorithms for the optimization of the liner technology.