Research focus
About the research
How can information-driven planning improve decision-making for sensing and control in distributed autonomous systems?
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The Laboratory for Intelligent Systems and Control (LISC) develops algorithms for information-driven path planning and control, active perception, and sensorimotor learning. Researchers formulate and apply adaptive dynamic programming, reinforcement learning, and nonparametric Bayesian models for target tracking and distributed sensor-network control. Projects include scalable learning algorithms for spiking neuronal networks and value-function approximation methods for multiscale dynamical systems.
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