Two-vehicle racing is natural example of a competitive dynamic game. As with most dynamic
games, there are many ways in which the underlying information pattern can be structured …

Autonomous agents should be able to coordinate with other agents without knowing their
intents ahead of time. While prior work has studied how agents can gather information about …

智能驾驶是交通和汽车领域未来发展的重要方向, 决策规划作为智能驾驶系统中的关键模块,
一直是其重点研究领域之一. 当前的研究热点正在从单车智能驾驶决策向混行交通场景下的多车 …

Interaction-aware trajectory planning is crucial for closing the gap between autonomous
racing cars and human racing drivers. Prior work has applied game theory as it provides …

Generating competitive strategies and performing continuous motion planning
simultaneously in an adversarial setting is a challenging problem. In addition, understanding …

This work proposes a policy learning algorithm for generalised feedback Nash equilibrium
seeking in $ N_P $-players non-cooperative dynamic games. We consider linear-quadratic …

In this paper, we propose an equilibrium-seeking algorithm for finding generalized Nash
equilibria of non-cooperative monotone convex quadratic games. Specifically, we recast the …

We present a novel algorithm for motion planning in complex, multi-agent scenarios in which
occlusions prevent all agents from seeing one another. In this setting, the fundamental …

They create plans to actively gather information about themselves, others, and the
environment, while simultaneously avoiding actions that lead to high uncertainty. They also …

We present an algorithm to solve for local Nash Equilibrium trajectories in the multi-agent
motion planning problem for self-interested agents. Our method models the problem as a …