46 citations · 48 across the 5 of their papers we have counts for
5 papers
Learning to Navigate from Scratch using World Models and Curiosity: the Good, the Bad, and the Ugly
Daria de Tinguy, Sven Remmery, Pietro Mazzaglia +2
Learning to navigate unknown environments from scratch is a challenging problem. This work presents a system that integrates world models with curiosity-driven exploration for auto…
Maximum Causal Entropy Inverse Constrained Reinforcement Learning
Mattijs Baert, Pietro Mazzaglia, Sam Leroux +1
When deploying artificial agents in real-world environments where they interact with humans, it is crucial that their behavior is aligned with the values, social norms or other req…
Object-Centric Scene Representations using Active Inference
Toon Van de Maele, Tim Verbelen, Pietro Mazzaglia +2
Representing a scene and its constituent objects from raw sensory data is a core ability for enabling robots to interact with their environment. In this paper, we propose a novel a…
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…
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…