  In this paper, we describe an integrated framework for autonomous decision
making in a dynamic and interactive environment. We model the interactions
between the ego agent and its operating environment as a two-player dynamic
game, and integrate cognitive behavioral models, Bayesian inference, and
receding-horizon optimal control to define a dynamically-evolving decision
strategy for the ego agent. Simulation examples representing autonomous vehicle
control in three traffic scenarios where the autonomous ego vehicle interacts
with a human-driven vehicle are reported.
