1 citations · 1 across the 3 of their papers we have counts for
5 papers
Sparsity Inducing Representations for Policy Decompositions
Ashwin Khadke, Hartmut Geyer
Policy Decomposition (PoDec) is a framework that lessens the curse of dimensionality when deriving policies to optimal control problems. For a given system representation, i.e. the…
Search Methods for Policy Decompositions
Ashwin Khadke, Hartmut Geyer
Computing optimal control policies for complex dynamical systems requires approximation methods to remain computationally tractable. Several approximation methods have been develop…
Policy Decomposition: Approximate Optimal Control with Suboptimality Estimates
Ashwin Khadke, Hartmut Geyer
Numerically computing global policies to optimal control problems for complex dynamical systems is mostly intractable. In consequence, a number of approximation methods have been d…
Using Deep Reinforcement Learning to Learn High-Level Policies on the ATRIAS Biped
Tianyu Li, Akshara Rai, Hartmut Geyer +1
Learning controllers for bipedal robots is a challenging problem, often requiring expert knowledge and extensive tuning of parameters that vary in different situations. Recently, d…
Bayesian Optimization Using Domain Knowledge on the ATRIAS Biped
Akshara Rai, Rika Antonova, Seungmoon Song +3
Controllers in robotics often consist of expert-designed heuristics, which can be hard to tune in higher dimensions. It is typical to use simulation to learn these parameters, but…