Learning Models of Adversarial Agent Behavior Under Partial Observability
Sean Ye,Manisha Natarajan,Zixuan Wu,Rohan Paleja,Letian Chen,Matthew C. Gombolay,Sean Ye,Manisha Natarajan,Zixuan Wu,Rohan Paleja,Letian Chen,Matthew C. Gombolay
The need for opponent modeling and tracking arises in several real-world scenarios, such as professional sports, video game design, and drug-trafficking interdiction. In this work, we present Graph based Adversarial Modeling with Mutual Information (GrAMMI) for modeling the behavior of an adversarial opponent agent. GrAMMI is a novel graph neural network (GNN) based approach that uses mutual infor...
