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GECCO
2006
Springer
159views Optimization» more  GECCO 2006»
15 years 7 months ago
Multi-step environment learning classifier systems applied to hyper-heuristics
Heuristic Algorithms (HA) are very widely used to tackle practical problems in operations research. They are simple, easy to understand and inspire confidence. Many of these HAs a...
Javier G. Marín-Blázquez, Sonia Schu...
BMCBI
2010
176views more  BMCBI 2010»
15 years 4 months ago
TargetSpy: a supervised machine learning approach for microRNA target prediction
Background: Virtually all currently available microRNA target site prediction algorithms require the presence of a (conserved) seed match to the 5' end of the microRNA. Recen...
Martin Sturm, Michael Hackenberg, David Langenberg...
WSC
1998
15 years 5 months ago
Military Simulation Worlds and Organizational Learning
The operational benefits of having a learning organization include at the very minimum increased organizational competitiveness and responsiveness in a given realm of competition....
Michael D. Proctor, Justin C. Gubler
SAB
2010
Springer
189views Optimization» more  SAB 2010»
15 years 1 months ago
TeXDYNA: Hierarchical Reinforcement Learning in Factored MDPs
Reinforcement learning is one of the main adaptive mechanisms that is both well documented in animal behaviour and giving rise to computational studies in animats and robots. In th...
Olga Kozlova, Olivier Sigaud, Christophe Meyer
UIST
2004
ACM
15 years 9 months ago
DART: a toolkit for rapid design exploration of augmented reality experiences
In this paper, we describe The Designerʼs Augmented Reality Toolkit (DART). DART is built on top of Macromedia Director, a widely used multimedia development environment. We summ...
Blair MacIntyre, Maribeth Gandy, Steven Dow, Jay D...