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CORR
2012
Springer
235views Education» more  CORR 2012»
12 years 3 months ago
An Incremental Sampling-based Algorithm for Stochastic Optimal Control
Abstract— In this paper, we consider a class of continuoustime, continuous-space stochastic optimal control problems. Building upon recent advances in Markov chain approximation ...
Vu Anh Huynh, Sertac Karaman, Emilio Frazzoli
CDC
2010
IEEE
151views Control Systems» more  CDC 2010»
13 years 2 months ago
Convergence of discrete-time approximations of constrained linear-quadratic optimal control problems
Abstract-- Continuous-time linear constrained optimal control problems are in practice often solved using discretization techniques, e.g. in model predictive control (MPC). This re...
Lanshan Han, M. Kanat Camlibel, Jong-Shi Pang, W. ...
HYBRID
2009
Springer
14 years 2 months ago
Optimal Boundary Control of Convention-Reaction Transport Systems with Binary Control Functions
We investigate a new approach for solving boundary control problems for dynamical systems that are governed by transport equations, when the control function is restricted to binar...
Falk M. Hante, Günter Leugering
ATAL
2007
Springer
14 years 1 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
CDC
2010
IEEE
160views Control Systems» more  CDC 2010»
13 years 2 months ago
Adaptive bases for Q-learning
Abstract-- We consider reinforcement learning, and in particular, the Q-learning algorithm in large state and action spaces. In order to cope with the size of the spaces, a functio...
Dotan Di Castro, Shie Mannor