17 search results - page 1 / 4 » Learning and anticipation in online dynamic optimization wit... |
GECCO
2007
Springer
13 years 10 months ago
2007
Springer
The focus of this paper is on how to design evolutionary algorithms (EAs) for solving stochastic dynamic optimization problems online, i.e. as time goes by. For a proper design, t...
GECCO
2005
Springer
13 years 10 months ago
2005
Springer
In this paper we focus on an important source of problem– difficulty in (online) dynamic optimization problems that has so far received significantly less attention than the tr...
GECCO
2006
Springer
13 years 8 months ago
2006
Springer
In reinforcement learning, an agent interacting with its environment strives to learn a policy that specifies, for each state it may encounter, what action to take. Evolutionary c...
COLT
2010
Springer
13 years 2 months ago
2010
Springer
We present a new family of subgradient methods that dynamically incorporate knowledge of the geometry of the data observed in earlier iterations to perform more informative gradie...
ECAL
2005
Springer
13 years 10 months ago
2005
Springer
An evolutionary reinforcement-learning algorithm, the operation of which was not associated with an optimality condition, was instantiated in an artificial organism. The algorithm ...