> The submission must train a machine learning model without relying heavily on human domain knowledge. A manually specified policy may not be used as a component of this model. Likewise, the reward function may not be changed (shaped) based on manually engineered, hard-coded functions of the state. For example, though a learned hierarchical controller is permitted, meta-controllers may not choose between two policies based on a manually specified function of the state, such as whether the agent has a certain item in its inventory. Similarly, additional rewards for approaching tree-like objects are not permitted, but rewards for encountering novel states (“curiosity rewards”) are permitted.

[1] https://gitlab.aicrowd.com/minerl/minerl-resources/blob/mast...