Results 81 to 90 of about 3,696,970 (268)

Learning Generative State Space Models for Active Inference

Frontiers in Computational Neuroscience, 2020
In this paper we investigate the active inference framework as a means to enable autonomous behavior in artificial agents. Active inference is a theoretical framework underpinning the way organisms act and observe in the real world.
Ozan Çatal, Samuel Wauthier, Cedric De Boom, Tim Verbelen, Bart Dhoedt   +4 more
doaj   +1 more source

Active inference, stressors, and psychological trauma: A neuroethological model of (mal)adaptive explore-exploit dynamics in ecological context [PDF]

, 2020
This paper offers a formal account of emotional inference and stress-related behaviour, using the notion of active inference. We formulate responses to stressful scenarios in terms of Bayesian belief-updating and subsequent policy selection; namely ...
Parr, Thomas, Friston, KJ, Linson, A, Linson, Adam, Friston, Karl J, Parr, T, Friston, Karl J.   +6 more
core   +1 more source

Gut microbiome and aging—A dynamic interplay of microbes, metabolites, and the immune system

FEBS Letters, EarlyView.
Age‐dependent shifts in microbial communities engender shifts in microbial metabolite profiles. These in turn drive shifts in barrier surface permeability of the gut and brain and induce immune activation. When paired with preexisting age‐related chronic inflammation this increases the risk of neuroinflammation and neurodegenerative diseases.
Aaron Mehl, Eran Blacher
wiley   +1 more source

Active Inference for Robotic Manipulation

CoRR, 2022
Robotic manipulation stands as a largely unsolved problem despite significant advances in robotics and machine learning in the last decades. One of the central challenges of manipulation is partial observability, as the agent usually does not know all physical properties of the environment and the objects it is manipulating in advance.
Tim Schneider, Boris Belousov, Hany Abdulsamad, Jan Peters 0001   +3 more
openaire   +2 more sources

Hyperosmotic stress induces PARP1‐mediated HPF1‐dependent mono(ADP‐ribosyl)ation

FEBS Letters, EarlyView.
Sorbitol‐induced hyperosmotic stress rapidly induces reversible mono(ADP‐ribosyl)ation (MARylation) on PARP1 without the signs of genotoxic signaling. We show that PARP1 autoMARylation is HPF1 dependent and forms hydroxylamine‐resistant O‐glycosidic linkages.
Anna Georgina Kopasz, Mihály Mérey, Rebeka Vásárhelyi, Ramóna Pék, Victor Imburchia, László Henn, Adrián Kószó, Nicholas D. Lakin, Ivan Ahel, Sébastien Huet, Ágnes Czibula, Gyula Timinszky   +11 more
wiley   +1 more source

The Active Inference Model of Coherence Therapy

Frontiers in Human Neuroscience, 2023
Coherence Therapy is an empirically derived experiential psychotherapy based on Psychological Constructivism. Symptoms are viewed as necessary output from an implicit model of the world.
D. Eric Chamberlin
doaj   +1 more source

Modelling stem cell differentiation related processes—A practical overview for biologists

FEBS Letters, EarlyView.
Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar, Xinqi Yan, Lucas F. Jansen Klomp, Stefano Schivo, Janine N. Post   +4 more
wiley   +1 more source

Active Inference and Intentional Behavior

Neural Computation
Abstract Recent advances in theoretical biology suggest that key definitions of basal cognition and sentient behavior may arise as emergent properties of in vitro cell cultures and neuronal networks. Such neuronal networks reorganize activity to demonstrate structured behaviors when embodied in structured information landscapes.
Karl J. Friston, Tommaso Salvatori, Takuya Isomura, Alexander Tschantz, Alex B. Kiefer, Tim Verbelen, Magnus T. Koudahl, Aswin Paul, Thomas Parr, Adeel Razi, Brett J. Kagan, Christopher L. Buckley, Maxwell J. D. Ramstead   +12 more
openaire   +4 more sources

Active Bayesian Causal Inference

Advances in Neural Information Processing Systems 35, 2022
Causal discovery and causal reasoning are classically treated as separate and consecutive tasks: one first infers the causal graph, and then uses it to estimate causal effects of interventions. However, such a two-stage approach is uneconomical, especially in terms of actively collected interventional data, since the causal query of interest may not ...
Christian Toth, Lars Lorch, Christian Knoll 0002, Andreas Krause 0001, Franz Pernkopf, Robert Peharz, Julius von Kügelgen   +6 more
openaire   +5 more sources

From pixels to planning: scale-free active inference. [PDF]

Front Netw Physiol
This paper describes a discrete state-space model and accompanying methods for generative modeling. This model generalizes partially observed Markov decision processes to include paths as latent variables, rendering it suitable for active inference and ...
Friston K, Heins C, Verbelen T, Da Costa L, Salvatori T, Markovic D, Tschantz A, Koudahl M, Buckley C, Parr T.   +9 more
europepmc   +2 more sources