Effects of sampling and horizon in predictive reinforcement learning

Pavel Osinenko, Dmitrii Dobriborsci

Plain reinforcement learning (RL) may be prone to loss of convergence, constraint violation, unexpected performance, etc. Commonly, RL agents undergo extensive learning stages to a…