System and method for online, task-aware opponent modeling in autonomous racing

A non-transitory computer-readable medium having program code recorded thereon for an online, task-aware opponent modeling in autonomous racing, the program code being executed by a processor and comprising:

• program code to concurrently train an opponent-aware policy and an opponent-aware encoder using reinforcement learning;
• program code to calculate, by the opponent-aware encoder, opponent encoding information according to prior opponent positions;
• program code to update learning parameters of the opponent-aware policy using the opponent encoding information from the opponent-aware encoder to predict actions;
• and
• program code to update a posterior network according to an auxiliary mutual information loss between the actions predicted by the opponent-aware policy and the opponent encoding information from the opponent-aware encoder.

A system for an online, task-aware opponent modeling in autonomous racing, the system comprising:

• a concurrent model training module to concurrently train an opponent-aware policy and an opponent-aware encoder using reinforcement learning;
• an opponent encoding model to calculate, by the opponent-aware encoder, opponent encoding information according to prior opponent positions;
• an ego-vehicle policy model to update learning parameters of the opponent-aware policy using the opponent encoding information from the opponent-aware encoder to predict actions;
• and
• a mutual information loss module to update a posterior network according to an auxiliary mutual information loss between the actions predicted by the opponent-aware policy and the opponent encoding information from the opponent-aware encoder.