no code implementations • 18 Feb 2023 • Hannes Eriksson, Debabrota Basu, Tommy Tram, Mina Alibeigi, Christos Dimitrakakis
Then, we propose a generic two-stage algorithm, MLEMTRL, to address the MTRL problem in discrete and continuous settings.
no code implementations • 17 Jun 2020 • Carl-Johan Hoel, Tommy Tram, Jonas Sjöberg
This paper investigates how a Bayesian reinforcement learning method can be used to create a tactical decision-making agent for autonomous driving in an intersection scenario, where the agent can estimate the confidence of its recommended actions.
no code implementations • 1 Aug 2019 • Tommy Tram, Ivo Batkovic, Mohammad Ali, Jonas Sjöberg
In this paper, we propose a decision making algorithm intended for automated vehicles that negotiate with other possibly non-automated vehicles in intersections.
no code implementations • 24 Oct 2018 • Tommy Tram, Anton Jansson, Robin Grönberg, Mohammad Ali, Jonas Sjöberg
Moreover, inferring information over time is important to distinguish between different intentions and is shown by comparing the collision rate between a Deep Recurrent Q-Network at 0. 85% and a Deep Q-learning at 1. 75%.