200 citations · 557 across the 42 of their papers we have counts for
9 papers · 1 filter
Exploring and Learning Structure: Active Inference Approach in Navigational Agents
Daria de Tinguy, Tim Verbelen, Bart Dhoedt
Drawing inspiration from animal navigation strategies, we introduce a novel computational model for navigation and mapping, rooted in biologically inspired principles. Animals exhi…
Learning Spatial and Temporal Hierarchies: Hierarchical Active Inference for navigation in Multi-Room Maze Environments
Daria de Tinguy, Toon Van de Maele, Tim Verbelen +1
Cognitive maps play a crucial role in facilitating flexible behaviour by representing spatial and conceptual relationships within an environment. The ability to learn and infer the…
Integrating cognitive map learning and active inference for planning in ambiguous environments
Toon Van de Maele, Bart Dhoedt, Tim Verbelen +1
Living organisms need to acquire both cognitive maps for learning the structure of the world and planning mechanisms able to deal with the challenges of navigating ambiguous enviro…
Inferring Hierarchical Structure in Multi-Room Maze Environments
Daria de Tinguy, Toon Van de Maele, Tim Verbelen +1
Cognitive maps play a crucial role in facilitating flexible behaviour by representing spatial and conceptual relationships within an environment. The ability to learn and infer the…
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…
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…
Disentangling What and Where for 3D Object-Centric Representations Through Active Inference
Toon Van de Maele, Tim Verbelen, Ozan Catal +1
Although modern object detection and classification models achieve high accuracy, these are typically constrained in advance on a fixed train set and are therefore not flexible to…
Deep Active Inference for Autonomous Robot Navigation
Ozan Çatal, Samuel Wauthier, Tim Verbelen +2
Active inference is a theory that underpins the way biological agent's perceive and act in the real world. At its core, active inference is based on the principle that the brain is…
Decoupled Learning of Environment Characteristics for Safe Exploration
Pieter Van Molle, Tim Verbelen, Steven Bohez +3
Reinforcement learning is a proven technique for an agent to learn a task. However, when learning a task using reinforcement learning, the agent cannot distinguish the characterist…