Efficient Steering

TNT members involved in this project:
Jun.-Prof. Dr.-Ing. Alexander Dockhorn

Developing believable multi-agent simulations often relies on the use of steering algorithms. In contrast to path-finding, steering algorithms make short-term choices on the next movement based on their local environment. While those are very performant, designing the behavior of steering agents in complex environments is a challenging task.

Previous work concentrated on single-objective steering, which makes it hard to define the objective such that the desired movement behavior emerges. At the TNT, we work on generalizing the steering framework to make it compatible with multi-objective task definitions and integrate performant decision-making algorithms. This results in smoother agent behavior and reduces the frequency of deadlock situations.

  • Conference Contributions
    • Lars Wagner, Christopher Olson, Alexander Dockhorn
      Generalizations of Steering - A Modular Design
      2022 IEEE Conference on Games (CoG), IEEE, pp. 1-4, 2022
    • Alexander Dockhorn, Sanaz Mostaghim, Martin Kirst, Martin Zettwitz
      Multi-Objective Optimization and Decision-Making in Context Steering
      2021 IEEE Conference on Games (CoG), IEEE, pp. 1-8, 2021
  • Journals
    • Alexander Dockhorn, Martin Kirst, Sanaz Mostaghim, Martin Wieczorek, Heiner Zille
      Evolutionary Algorithm for Parameter Optimization of Context Steering Agents
      IEEE Transactions on Games, IEEE, pp. 1-12, 2022