16 citations · 77 across the 21 of their papers we have counts for
4 papers · 1 filter
Synthesizing Safe Policies under Probabilistic Constraints with Reinforcement Learning and Bayesian Model Checking
Lenz Belzner, Martin Wirsing
We propose to leverage epistemic uncertainty about constraint satisfaction of a reinforcement learner in safety critical domains. We introduce a framework for specification of requ…
Memory Bounded Open-Loop Planning in Large POMDPs using Thompson Sampling
Thomy Phan, Lenz Belzner, Marie Kiermeier +3
State-of-the-art approaches to partially observable planning like POMCP are based on stochastic tree search. While these approaches are computationally efficient, they may still co…
Distributed Policy Iteration for Scalable Approximation of Cooperative Multi-Agent Policies
Thomy Phan, Kyrill Schmid, Lenz Belzner +3
Decision making in multi-agent systems (MAS) is a great challenge due to enormous state and joint action spaces as well as uncertainty, making centralized control generally infeasi…
Monte Carlo Action Programming
Lenz Belzner
This paper proposes Monte Carlo Action Programming, a programming language framework for autonomous systems that act in large probabilistic state spaces with high branching factors…