150 citations · 548 across the 51 of their papers we have counts for
55 papers
Shielded Reinforcement Learning for Hybrid Systems
Asger Horn Brorholt, Peter Gjøl Jensen, Kim Guldstrand Larsen +2
Safe and optimal controller synthesis for switched-controlled hybrid systems, which combine differential equations and discrete changes of the system's state, is known to be intric…
Energy Consumption Optimization in Radio Access Networks (ECO-RAN)
Anders Mariegaard, Kim G. Larsen, Marco Muniz +1
In recent years, mobile network operators are showing interest in reducing energy consumption. Toward this goal, in cooperation with the Danish company 2Operate we have developed a…
MM Algorithms to Estimate Parameters in Continuous-time Markov Chains
Giovanni Bacci, Anna Ingólfsdóttir, Kim G. Larsen +1
Continuous-time Markov chains (CTMCs) are popular modeling formalism that constitutes the underlying semantics for real-time probabilistic systems such as queuing networks, stochas…
Timed I/O Automata: It is never too late to complete your timed specification theory
Martijn A. Goorden, Kim G. Larsen, Axel Legay +3
A specification theory combines notions of specifications and implementations with a satisfaction relation, a refinement relation and a set of operators supporting stepwise design.…
Optimality-preserving Reduction of Chemical Reaction Networks
Kim G. Larsen, Daniele Toller, Mirco Tribastone +2
Across many disciplines, chemical reaction networks (CRNs) are an established population model defined as a system of coupled nonlinear ordinary differential equations. In many app…
Automata Learning meets Shielding
Martin Tappler, Stefan Pranger, Bettina Könighofer +3
Safety is still one of the major research challenges in reinforcement learning (RL). In this paper, we address the problem of how to avoid safety violations of RL agents during exp…