51 search results - page 5 / 11 » Optimizing walking controllers for uncertain inputs and envi... |
TFS
2011
13 years 2 months ago
2011
—Reinforcement learning (RL) is a valuable learning method when the systems require a selection of control actions whose consequences emerge over long periods for which input– ...
PUK
2000
13 years 9 months ago
2000
This paper proposes a new planning architecture for agents operating in uncertain and dynamic environments. Decisiontheoretic planning has been recognized as a useful tool for rea...
CDC
2010
IEEE
13 years 2 months ago
2010
IEEE
Abstract-- In robot deployment problems, the fundamental issue is to optimize a steady state performance measure that depends on the spatial configuration of a group of robots. For...
AAAI
2008
13 years 10 months ago
2008
When controlling dynamic systems, such as mobile robots in uncertain environments, there is a trade off between risk and reward. For example, a race car can turn a corner faster b...
GECCO
2005
Springer
14 years 1 months ago
2005
Springer
We present a Genetic Programming approach to evolve cooperative controllers for teams of UAVs. Our focus is a collaborative search mission in an uncertain and/or hostile environme...