Contingency planning, wherein an agent generates a set of possible plans conditioned on
the outcome of an uncertain event, is an increasingly popular way for robots to act under …

In this work, we develop a scalable, local tra-jectory optimization algorithm that enables
robots to interact with other robots. It has been shown that agents' interactions can be …

Robots and autonomous systems must interact with one another and their environment to
provide high-quality services to their users. Dynamic game theory provides an expressive …

Many autonomous agents, such as intelligent vehicles, are inherently required to interact
with one another. Game theory provides a natural mathematical tool for robot motion …

Robots deployed to the real world must be able to interact with other agents in their
environment. Dynamic game theory provides a powerful mathematical framework for …

Effectively predicting intent and behavior requires inferring leadership in multi-agent
interactions. Dynamic games provide an expressive theoretical framework for modeling …

In multi-agent dynamic games, the Nash equilibrium state trajectory of each agent is
determined by its cost function and the information pattern of the game. However, the cost …

In this work, we propose a numerical method for the solution of local generalized Nash
equilibria (GNE) for the class of open-loop general-sum dynamic games for agents with …

Although dynamic games provide a rich paradigm for modeling agents' interactions, solving
these games for real-world applications is often challenging. Many real-wold interactive …

Mathematical Program Networks (MPNs) are introduced in this work. A MPN is a collection
of interdependent Mathematical Programs (MPs) which are to be solved simultaneously …