200 citations · 557 across the 42 of their papers we have counts for
7 papers · 1 filter
Choreographer: Learning and Adapting Skills in Imagination
Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt +2
Unsupervised skill learning aims to learn a rich repertoire of behaviors without external supervision, providing artificial agents with the ability to control and influence the env…
Disentangling Shape and Pose for Object-Centric Deep Active Inference Models
Stefano Ferraro, Toon Van de Maele, Pietro Mazzaglia +2
Active inference is a first principles approach for understanding the brain in particular, and sentient agents in general, with the single imperative of minimizing free energy. As…
Learning Generative Models for Active Inference using Tensor Networks
Samuel T. Wauthier, Bram Vanhecke, Tim Verbelen +1
Active inference provides a general framework for behavior and learning in autonomous agents. It states that an agent will attempt to minimize its variational free energy, defined…
Mastering the Unsupervised Reinforcement Learning Benchmark from Pixels
Sai Rajeswar, Pietro Mazzaglia, Tim Verbelen +4
Controlling artificial agents from visual sensory data is an arduous task. Reinforcement learning (RL) algorithms can succeed but require large amounts of interactions between the…
Home Run: Finding Your Way Home by Imagining Trajectories
Daria de Tinguy, Pietro Mazzaglia, Tim Verbelen +1
When studying unconstrained behaviour and allowing mice to leave their cage to navigate a complex labyrinth, the mice exhibit foraging behaviour in the labyrinth searching for rewa…
Audio-guided Album Cover Art Generation with Genetic Algorithms
James Marien, Sam Leroux, Bart Dhoedt +1
Over 60,000 songs are released on Spotify every day, and the competition for the listener's attention is immense. In that regard, the importance of captivating and inviting cover a…
The Free Energy Principle for Perception and Action: A Deep Learning Perspective
Pietro Mazzaglia, Tim Verbelen, Ozan Çatal +1
The free energy principle, and its corollary active inference, constitute a bio-inspired theory that assumes biological agents act to remain in a restricted set of preferred states…