Developing autonomous agents that learn from their environment
We are an academic research team in the Signal Processing Systems group (EE department) at Eindhoven University of Technology. Our main research interest is in developing autonomous agents that learn through interacting with their environment and using these agents to automate the development of new signal processing systems. Typical application areas include (medical) device personalization, automated vehicle control and robotics. Our research is strongly inspired by developments in Bayesian machine learning and Computational Neurosciences. An important research focus area is our quest to develop (machine learning) technology to support situated personalization of audio processing systems such as hearing aids. We “eat our own dogfood” by immersing ourselves in complex acoustic situations and use our own tools to optimize audio processing algorithms under in-situ conditions. This leads to new problems that drive our next research steps.
News
Meet some of our Researchers
Recent Publications
Our most recent peer reviewed publications
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Context-Aware Preference Learning System Based on Dirichlet Process Gaussian Mixture Model
(2024) -
Toward Design of Synthetic Active Inference Agents by Mere Mortals
(2024) -
Principled Pruning of Bayesian Neural Networks through Variational Free Energy Minimization
IEEE Open Journal of Signal Processing (2024) -
Information-seeking polynomial NARX model-predictive control through expected free energy minimization
IEEE Control Systems Letters (2024) -
Efficient Bayesian Inference By Conjugate-Computation Variational Message Passing
(2023)
Contact
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Teamleadbert.de.vries@ tue.nl