Off-policy reinforcement learning is aimed at efficiently reusing data samples gathered in the past, which is an essential problem for physically grounded AI as experiments are us...
Based on Information Theory, optimal feature selection should be carried out by searching Markov blankets. In this paper, we formally analyze the current Markov blanket discovery ...
Current studies have demonstrated that the representational power of predictive state representations (PSRs) is at least equal to the one of partially observable Markov decision p...
Abdeslam Boularias, Masoumeh T. Izadi, Brahim Chai...
Multi-agent teams must be capable of selecting the most beneficial teammates for different situations. Multi-dimensional trustworthiness assessments have been shown significantly ...
Jaesuk Ahn, Xin Sui, David DeAngelis, K. Suzanne B...
We present an unsupervised speaker identification system for personal annotations of conversations and meetings. The system dynamically learns new speakers and recognizes already k...
Mirco Rossi, Oliver Amft, Martin Kusserow, Gerhard...