We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carryin...
—Wireless mesh networks (WMNs) are evolving as a key technology for next-generation wireless networks showing raid progress and numerous applications. These networks have the pot...
For a stationary stochastic process {Xn} with values in some set A, a finite word w AK is called a memory word if the conditional probability of X0 given the past is constant on t...
— In the past, there has been a tremendous advance in the area of simultaneous localization and mapping (SLAM). However, there are relatively few approaches for incorporating pri...
Michael Karg, Kai M. Wurm, Cyrill Stachniss, Klaus...
We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background kn...