Abstract: Embodiments described herein provide for revising radiation therapy treatment plans, and in particular, revising beam angles used during radiation therapy treatment. A computer may receive a radiation therapy treatment plan based on a particular patient's diagnosis. The computer may use a machine learning model to revise radiation therapy treatment parameters such as a beam angle indicating a direction of radiation into the patient. The machine learning model may use reinforcement learning to optimize an initial beam angle from the radiation therapy treatment plan, revising the beam angle. The performance of the machine learning model is measured against metrics including fulfilling dosimetric clinical goals. The machine learning model may present the revised beam angle for display to a medical professional, or transmit the revised beam angle to downstream applications to further revise the radiation therapy treatment plan.