4 citations · 13 across the 11 of their papers we have counts for
3 papers · 1 filter
Reactive Exploration to Cope with Non-Stationarity in Lifelong Reinforcement Learning
Christian Steinparz, Thomas Schmied, Fabian Paischer +5
In lifelong learning, an agent learns throughout its entire life without resets, in a constantly changing environment, as we humans do. Consequently, lifelong learning comes with a…
History Compression via Language Models in Reinforcement Learning
Fabian Paischer, Thomas Adler, Vihang Patil +5
In a partially observable Markov decision process (POMDP), an agent typically uses a representation of the past to approximate the underlying MDP. We propose to utilize a frozen Pr…
A Globally Convergent Evolutionary Strategy for Stochastic Constrained Optimization with Applications to Reinforcement Learning
Youssef Diouane, Aurelien Lucchi, Vihang Patil
Evolutionary strategies have recently been shown to achieve competing levels of performance for complex optimization problems in reinforcement learning. In such problems, one often…