153 citations · 557 across the 25 of their papers we have counts for
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Adaptation through prediction: multisensory active inference torque control
Cristian Meo, Giovanni Franzese, Corrado Pezzato +2
Adaptation to external and internal changes is major for robotic systems in uncertain environments. Here we present a novel multisensory active inference torque controller for indu…
Active Inference in Robotics and Artificial Agents: Survey and Challenges
Pablo Lanillos, Cristian Meo, Corrado Pezzato +8
Active inference is a mathematical framework which originated in computational neuroscience as a theory of how the brain implements action, perception and learning. Recently, it ha…
Training Deep Spiking Auto-encoders without Bursting or Dying Neurons through Regularization
Justus F. Hübotter, Pablo Lanillos, Jakub M. Tomczak
Spiking neural networks are a promising approach towards next-generation models of the brain in computational neuroscience. Moreover, compared to classic artificial neural networks…
Deep Active Inference for Pixel-Based Discrete Control: Evaluation on the Car Racing Problem
Niels van Hoeffelen, Pablo Lanillos
Despite the potential of active inference for visual-based control, learning the model and the preferences (priors) while interacting with the environment is challenging. Here, we…
Robot Localization and Navigation through Predictive Processing using LiDAR
Daniel Burghardt, Pablo Lanillos
Knowing the position of the robot in the world is crucial for navigation. Nowadays, Bayesian filters, such as Kalman and particle-based, are standard approaches in mobile robotics.…
Neuroscience-inspired perception-action in robotics: applying active inference for state estimation, control and self-perception
Pablo Lanillos, Marcel van Gerven
Unlike robots, humans learn, adapt and perceive their bodies by interacting with the world. Discovering how the brain represents the body and generates actions is of major importan…
Multimodal VAE Active Inference Controller
Cristian Meo, Pablo Lanillos
Active inference, a theoretical construct inspired by brain processing, is a promising alternative to control artificial agents. However, current methods do not yet scale to high-d…