Scenario-Game ADMM: A Parallelized Scenario-Based Solver for Stochastic Noncooperative Games

Decision-making in multi-player games can be extremely challenging, particularly under uncertainty. In this work, we propose a new sample-based approximation to a class of stochastic, general-sum, pure Nash games, where each player has an expected-value objective and a set of chance constraints. This new approximation scheme inherits the...

Bepalen luchtverontreiniging door verkeer met behulp van 3D-geo-informatie

Eerder publiceerden we in Geo-Info over onze methode om 3D-data zoals nodig in geluidsimulaties automatisch te genereren uit landsdekkende gegevens zoals BAG, BGT en hoogtepunten [1]. Deze geluidsimulaties zijn gebaseerd op gestandaardiseerde rekenvoorschriften voor geluids- belasting. Ook het berekenen van de luchtkwaliteit ten gevolge van...

Cost Inference for Feedback Dynamic Games from Noisy Partial State Observations and Incomplete Trajectories

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 and trajectory of each agent may be unavailable to the other agents. Prior work on using partial observations to infer the costs in dynamic games assumes an open-loop...