no code implementations • 25 Jan 2024 • Jan Dohmen, Frank Röder, Manfred Eppe
One problem with researching cognitive modeling and reinforcement learning (RL) is that researchers spend too much time on setting up an appropriate computational framework for their experiments.
1 code implementation • 18 Nov 2022 • Frank Röder, Manfred Eppe
To evaluate our approach, we propose a collection of benchmark environments for action correction in language-conditioned reinforcement learning, utilizing a synthetic instructor to generate language goals and their corresponding corrections.
2 code implementations • 8 Apr 2022 • Frank Röder, Manfred Eppe, Stefan Wermter
We show that hindsight instructions improve the learning performance, as expected.
1 code implementation • 7 May 2020 • Frank Röder, Manfred Eppe, Phuong D. H. Nguyen, Stefan Wermter
Hierarchical abstraction and curiosity-driven exploration are two common paradigms in current reinforcement learning approaches to break down difficult problems into a sequence of simpler ones and to overcome reward sparsity.