Influence of video content type on the usefulness of reinforcement learning algorithms in DASH systems

The article presents the result of research on DASH (Dynamic Adaptive Streaming over HTTP) systems. In proposed solution, adaptive algorithm is based RL (Reinforcement Learning) paradigm. Pensieve was chosen as basis for tests. This widely discussed in scientific literature and therefore study analysis its properties useful a wide range solutions using DASH. main contribution presented test results to development knowledge video streaming services consists impact characteristics materials effectiveness adaptation process implemented by developed model. show that this influence should not be omitted any in-depth analyses