4 papers · 1 filter
Structure Matters: Dynamic Policy Gradient
Sara Klein, Xiangyuan Zhang, Tamer BaÅar +2
In this work, we study -discounted infinite-horizon tabular Markov decision processes (MDPs) and introduce a framework called dynamic policy gradient (DynPG). The framework dir…
On the mean field limit of consensus based methods
Marvin KoÃ, Simon Weissmann, Jakob Zech
Consensus based optimization (CBO) employs a swarm of particles evolving as a system of stochastic differential equations (SDEs). Recently, it has been adapted to yield a derivativ…
Beyond Stationarity: Convergence Analysis of Stochastic Softmax Policy Gradient Methods
Sara Klein, Simon Weissmann, Leif Döring
Markov Decision Processes (MDPs) are a formal framework for modeling and solving sequential decision-making problems. In finite-time horizons such problems are relevant for instanc…
On the mean-field limit for Stein variational gradient descent: stability and multilevel approximation
Simon Weissmann, Jakob Zech
In this paper we propose and analyze a novel multilevel version of Stein variational gradient descent (SVGD). SVGD is a recent particle based variational inference method. For Baye…