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AAAI
2008
15 years 6 months ago
Adaptive Importance Sampling with Automatic Model Selection in Value Function Approximation
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...
Hirotaka Hachiya, Takayuki Akiyama, Masashi Sugiya...
AIPS
2007
15 years 6 months ago
Learning to Plan Using Harmonic Analysis of Diffusion Models
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,...
IROS
2006
IEEE
97views Robotics» more  IROS 2006»
15 years 10 months ago
A quasi-passive model of human leg function in level-ground walking
- 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...
Ken Endo, Daniel Paluska, Hugh M. Herr
138
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TCS
2008
15 years 3 months ago
GemCell: A generic platform for modeling multi-cellular biological systems
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...
DBPL
1991
Springer
76views Database» more  DBPL 1991»
15 years 7 months ago
A Functional DBPL Revealing High Level Optimizations
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...
Martin Erwig, Udo W. Lipeck