25 citations · 30 across the 11 of their papers we have counts for
4 papers · 1 filter
Learning Temporally Extended Skills in Continuous Domains as Symbolic Actions for Planning
Jan Achterhold, Markus Krimmel, Joerg Stueckler
Problems which require both long-horizon planning and continuous control capabilities pose significant challenges to existing reinforcement learning agents. In this paper we introd…
Explore the Context: Optimal Data Collection for Context-Conditional Dynamics Models
Jan Achterhold, Joerg Stueckler
In this paper, we learn dynamics models for parametrized families of dynamical systems with varying properties. The dynamics models are formulated as stochastic processes condition…
Sample-efficient Cross-Entropy Method for Real-time Planning
Cristina Pinneri, Shambhuraj Sawant, Sebastian Blaes +4
Trajectory optimizers for model-based reinforcement learning, such as the Cross-Entropy Method (CEM), can yield compelling results even in high-dimensional control tasks and sparse…
Planning from Images with Deep Latent Gaussian Process Dynamics
Nathanael Bosch, Jan Achterhold, Laura Leal-Taixé +1
Planning is a powerful approach to control problems with known environment dynamics. In unknown environments the agent needs to learn a model of the system dynamics to make plannin…