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...
Standard hybrid learners that use domain knowledge require stronger knowledge that is hard and expensive to acquire. However, weaker domain knowledge can benefit from prior knowle...
—Adaptive Turbo frequency-domain channel estimation is investigated for single-carrier (SC) multi-user detection in the presence of unknown co-channel interference (CCI). We prop...
In this paper, we demonstrate that the main standard optimization techniques dependency directed backtracking and model merging can be adapted to description logics with concrete ...
Developing adaptive internet based learning courses usually requires a lot of programming efforts to provide session management, keeping track of the learners current state, and ad...
Gerhard Weber, Hans-Christian Kuhl, Stephan Weibel...