1 code implementation • 16 Jul 2023 • Giacomo Arcieri, Cyprien Hoelzl, Oliver Schwery, Daniel Straub, Konstantinos G. Papakonstantinou, Eleni Chatzi
The POMDP with uncertain parameters is then solved via deep RL techniques with the parameter distributions incorporated into the solution via domain randomization, in order to develop solutions that are robust to model uncertainty.
1 code implementation • 15 Dec 2022 • Giacomo Arcieri, Cyprien Hoelzl, Oliver Schwery, Daniel Straub, Konstantinos G. Papakonstantinou, Eleni Chatzi
We present a framework to estimate POMDP transition and observation model parameters directly from available data, via Markov Chain Monte Carlo (MCMC) sampling of a Hidden Markov Model (HMM) conditioned on actions.
1 code implementation • 25 Oct 2021 • Giacomo Arcieri, David Wölfle, Eleni Chatzi
The main contribution of this work lies precisely in assessing the model influence on the performance of RL algorithms.