Off-policy reinforcement learning is aimed at efficiently reusing data samples gathered in the past, which is an essential problem for physically grounded AI as experiments are us...
This paper summarizes research on a new emerging framework for learning to plan using the Markov decision process model (MDP). In this paradigm, two approaches to learning to plan...
Sridhar Mahadevan, Sarah Osentoski, Jeffrey Johns,...
- In this paper, we seek to understand how leg muscles and tendons work mechanically during walking in order to motivate the design of efficient robotic legs. We hypothesize that a...
The mass and complexity of biological information requires computer-aided simulation and analysis to help scientists achieve understanding and guide experimentation. Although livi...
Hila Amir-Kroll, Avital Sadot, Irun R. Cohen, Davi...
We present a functional DBPL in the style of FP that facilitates the definition of precise semantics and opens up opportunities for far-reaching optimizations. The language is int...