SYSTEMS AND METHODS FOR MANAGING ASSIGNMENTS OF TASKS FOR WORK MACHINES USING MACHINE LEARNING

Systems and methods are disclosed for managing task assignments for a plurality of work machines at a site. An assignment engine may: receive first state data for a work machine including historical data, operating condition, and location data, and second state data for the site including characteristic data for materials and a plurality of available tasks; predict performance data and energy consumption data of the work machine for a task; select a task for the work machine by inputting first state data and second state data into a trained reinforcement-learning model, wherein: the model has been trained to learn an assignment policy that optimizes a reward function such that the learned policy selects a task for at least one work machine from the plurality of tasks available at the site; and cause the at least one work machine to be operated according to the at least one task assignment.