92 citations · 174 across the 10 of their papers we have counts for
11 papers
Theory of Mind Using Active Inference: A Framework for Multi-Agent Cooperation
Riddhi J. Pitliya, Ozan Çatal, Toon Van de Maele +2
Theory of Mind (ToM) -- the ability to understand that others can have differing knowledge and goals -- enables agents to reason about others' beliefs while planning their own acti…
Mobile Manipulation with Active Inference for Long-Horizon Rearrangement Tasks
Corrado Pezzato, Ozan Çatal, Toon Van de Maele +2
Despite growing interest in active inference for robotic control, its application to complex, long-horizon tasks remains untested. We address this gap by introducing a fully hierar…
AXIOM: Learning to Play Games in Minutes with Expanding Object-Centric Models
Conor Heins, Toon Van de Maele, Alexander Tschantz +11
Current deep reinforcement learning (DRL) approaches achieve state-of-the-art performance in various domains, but struggle with data efficiency compared to human learning, which le…
Multi-Modal MPPI and Active Inference for Reactive Task and Motion Planning
Yuezhe Zhang, Corrado Pezzato, Elia Trevisan +3
Task and Motion Planning (TAMP) has made strides in complex manipulation tasks, yet the execution robustness of the planned solutions remains overlooked. In this work, we propose a…
Unbiased Active Inference for Classical Control
Mohamed Baioumy, Corrado Pezzato, Riccardo Ferrari +1
Active inference is a mathematical framework that originated in computational neuroscience. Recently, it has been demonstrated as a promising approach for constructing goal-driven…
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…
Towards Stochastic Fault-tolerant Control using Precision Learning and Active Inference
Mohamed Baioumy, Corrado Pezzato, Carlos Hernandez Corbato +2
This work presents a fault-tolerant control scheme for sensory faults in robotic manipulators based on active inference. In the majority of existing schemes, a binary decision of w…
Fault-tolerant Control of Robot Manipulators with Sensory Faults using Unbiased Active Inference
Mohamed Baioumy, Corrado Pezzato, Riccardo Ferrari +2
This work presents a novel fault-tolerant control scheme based on active inference. Specifically, a new formulation of active inference which, unlike previous solutions, provides u…
Active Inference and Behavior Trees for Reactive Action Planning and Execution in Robotics
Corrado Pezzato, Carlos Hernandez Corbato, Stefan Bonhof +1
We propose a hybrid combination of active inference and behavior trees (BTs) for reactive action planning and execution in dynamic environments, showing how robotic tasks can be fo…
A Novel Adaptive Controller for Robot Manipulators based on Active Inference
Corrado Pezzato, Riccardo Ferrari, Carlos Hernandez
More adaptive controllers for robot manipulators are needed, which can deal with large model uncertainties. This paper presents a novel active inference controller (AIC) as an adap…