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» Approximate controllability of a reaction-diffusion system
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ATAL
2007
Springer
14 years 4 months ago
Model-based function approximation in reinforcement learning
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Nicholas K. Jong, Peter Stone
ICRA
2003
IEEE
110views Robotics» more  ICRA 2003»
14 years 3 months ago
Template based control of hexapedal running
In this paper, we introduce a new hexapedal locomotion controller that simulation evidence suggests will be capable of driving our RHex robot at speeds exceeding five body length...
Uluc Saranli, Daniel E. Koditschek
ATAL
2008
Springer
13 years 12 months ago
Dynamics based control with PSRs
We present an extension of the Dynamics Based Control (DBC) paradigm to environment models based on Predictive State Representations (PSRs). We show an approximate greedy version ...
Ariel Adam, Zinovi Rabinovich, Jeffrey S. Rosensch...
ICTAI
2008
IEEE
14 years 4 months ago
The Performance of Approximating Ordinary Differential Equations by Neural Nets
—The dynamics of many systems are described by ordinary differential equations (ODE). Solving ODEs with standard methods (i.e. numerical integration) needs a high amount of compu...
Josef Fojdl, Rüdiger W. Brause
ATAL
2005
Springer
14 years 3 months ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson