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NIPS
1997
15 years 8 months ago
Reinforcement Learning with Hierarchies of Machines
We present a new approach to reinforcement learning in which the policies considered by the learning process are constrained by hierarchies of partially specified machines. This ...
Ronald Parr, Stuart J. Russell
173
Voted
TIP
2008
109views more  TIP 2008»
15 years 6 months ago
Iterative Rate-Distortion Optimization of H.264 With Constant Bit Rate Constraint
In this paper, we apply the primal-dual decomposition and subgradient projection methods to solve the rate-distortion optimization problem with the constant bit rate constraint. Th...
Cheolhong An, Truong Q. Nguyen
IROS
2009
IEEE
206views Robotics» more  IROS 2009»
16 years 1 months ago
Bayesian reinforcement learning in continuous POMDPs with gaussian processes
— Partially Observable Markov Decision Processes (POMDPs) provide a rich mathematical model to handle realworld sequential decision processes but require a known model to be solv...
Patrick Dallaire, Camille Besse, Stéphane R...
GECCO
2009
Springer
16 years 1 months ago
An evolutionary approach to planning IEEE 802.16 networks
Efficient and effective deployment of IEEE 802.16 networks to service an area of users with certain traffic demands is an important network planning problem. We resort to an evol...
Ting Hu, Yuanzhu Peter Chen, Wolfgang Banzhaf, Rob...
159
Voted
GECCO
2009
Springer
200views Optimization» more  GECCO 2009»
16 years 1 months ago
Optimization of the trading rule in foreign exchange using genetic algorithm
The generation of profitable trading rules for Foreign Exchange (FX) investments is a difficult but popular problem. The use of Machine Learning in this problem allows us to obtai...
Akinori Hirabayashi, Claus de Castro Aranha, Hitos...