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A Multi-Agent Simulation of Serious Games to Predict Their Impact on E-Learning Processes
Identification of the Students Learning Process During Education Robotics Activities
Simulation-driven machine learning for robotics and automation
Simultaneous estimation of rewards and dynamics in inverse reinforcement learning problems
Latent State-Space Models for Control
Schwingkomfortbewertung in Straßenbahnen mittels Maschinellen Lernens
Deep Reinforcement Learning for the Navigation of Neurovascular Catheters
A framework for current signal based bearing fault detection of permanent magnet synchronous motors
Artificial Intelligence for Spectral Analysis: a Comprehensive Framework
Smart Event Forecast for Seaports (SMECS) : Schlussbericht : Projektlaufzeit: 01.09.2017-29.02.2020
Reinforcement learning to adjust parametrized motor primitives to new situations
Combining learning and structure for robotic manipulation