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GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
13 years 5 months ago
Uncertainty handling CMA-ES for reinforcement learning
The covariance matrix adaptation evolution strategy (CMAES) has proven to be a powerful method for reinforcement learning (RL). Recently, the CMA-ES has been augmented with an ada...
Verena Heidrich-Meisner, Christian Igel
HICSS
2003
IEEE
123views Biometrics» more  HICSS 2003»
14 years 23 days ago
Issues in Rational Planning in Multi-Agent Settings
We adopt the decision-theoretic principle of expected utility maximization as a paradigm for designing autonomous rational agents operating in multi-agent environments. We use the...
Piotr J. Gmytrasiewicz
AIPS
2000
13 years 8 months ago
On-line Scheduling via Sampling
1 We consider the problem of scheduling an unknown sequence of tasks for a single server as the tasks arrive with the goal off maximizing the total weighted value of the tasks serv...
Hyeong Soo Chang, Robert Givan, Edwin K. P. Chong
ATAL
2009
Springer
14 years 2 months ago
SarsaLandmark: an algorithm for learning in POMDPs with landmarks
Reinforcement learning algorithms that use eligibility traces, such as Sarsa(λ), have been empirically shown to be effective in learning good estimated-state-based policies in pa...
Michael R. James, Satinder P. Singh
ATAL
2010
Springer
13 years 8 months ago
Augmenting appearance-based localization and navigation using belief update
Appearance-based localization compares the current image taken from a robot's camera to a set of pre-recorded images in order to estimate the current location of the robot. S...
George Chrysanthakopoulos, Guy Shani