Mart Kartasev — accepted AI-conference papers

2024

Improving the Performance of Learned Controllers in Behavior Trees Using Value Function Estimates at Switching Boundaries

RA-L 2024

Behavior trees offer a modular approach to developing an overall controller from a set of sub-controllers that solve different sub-problems. These sub-controllers can be created using various methods, such as classical model-based control or reinforcement learning (RL). To achieve the overall goal,

Cited by 4 Source ↗Scholar ↗

2023

Improving the Performance of Backward Chained Behavior Trees that use Reinforcement Learning

Mart Kartasev, Justin Salér, Petter Ögren

IROS 2023poster

In this paper we show how to improve the performance of backward chained behavior trees (BTs) that include policies trained with reinforcement learning (RL). BTs represent a hierarchical and modular way of combining control policies into higher level control policies. Backward chaining is a design p…

Cited by 8 Source ↗code ↗Scholar ↗