公开(公告)号：US20240403651A1

公开(公告)日：2024-12-05

申请号：US18328174

申请日：2023-06-02

Applicant: Adobe Inc.

Inventor： Shripad Vilasrao Deshmukh ,  Arpan Dasgupta ,  Balaji Krishnamurthy ,  Chirag Agarwal ,  Georgios Theocharous ,  Jayakumar Subramanian

IPC: G06N3/092

Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media that provide a trajectory-based explainability framework for reinforcement learning models. For example, the disclosed systems generate trajectory clusters from trajectories utilized to train a reinforcement learning agent. In some embodiments, the disclosed system generates a complementary target data set by removing a target trajectory cluster from the trajectory clusters. In some cases, the disclosed system trains a test reinforcement learning agent utilizing the complementary target data set and generates a cluster attribution by comparing the result of the test reinforcement learning agent with the result of the reinforcement learning agent.