Results 51 to 60 of about 139,336 (244)

Thoughtseeds: A Hierarchical and Agentic Framework for Investigating Thought Dynamics in Meditative States

Entropy
The Thoughtseeds Framework introduces a novel computational approach to modeling thought dynamics in meditative states, conceptualizing thoughtseeds as dynamic attentional agents that integrate information.
Prakash Chandra Kavi, Gorka Zamora-López, Daniel Ari Friedman, Gustavo Patow   +3 more
doaj   +1 more source

Shared Protentions in Multi-Agent Active Inference

Entropy
In this paper, we unite concepts from Husserlian phenomenology, the active inference framework in theoretical biology, and category theory in mathematics to develop a comprehensive framework for understanding social action premised on shared goals.
Mahault Albarracin, Riddhi J. Pitliya, Toby St. Clere Smithe, Daniel Ari Friedman, Karl Friston, Maxwell J. D. Ramstead   +5 more
doaj   +1 more source

Active Inference is a Subtype of Variational Inference

CoRR
Automated decision-making under uncertainty requires balancing exploitation and exploration. Classical methods treat these separately using heuristics, while Active Inference unifies them through Expected Free Energy (EFE) minimization. However, EFE minimization is computationally expensive, limiting scalability. We build on recent theory recasting EFE
Wouter W. L. Nuijten, Mykola Lukashchuk
openaire   +2 more sources

Serum Myonectin Levels Are Positively Associated With Physical Function and Lower Frailty‐Related Limitation in Maintenance Hemodialysis Patients: A Cross‐Sectional Study

Therapeutic Apheresis and Dialysis, EarlyView.
ABSTRACT Background Maintenance hemodialysis (MHD) patients frequently suffer from frailty, characterized by reduced physical function and poor prognosis. Myokines, such as myonectin, secreted by muscle, are emerging regulators of systemic health. This study investigated the relationship between serum myonectin, adipokines (adiponectin, omentin), and ...
Kenichi Kono, Yoshifumi Moriyama, Koji Ohashi, Naoya Otaka, Minako Tatsumi, Toyoaki Murohara, Noriyuki Ouchi, Satoru Oshima   +7 more
wiley   +1 more source

Active Statistical Inference

CoRR
Inspired by the concept of active learning, we propose active inference$\unicode{x2013}$a methodology for statistical inference with machine-learning-assisted data collection. Assuming a budget on the number of labels that can be collected, the methodology uses a machine learning model to identify which data points would be most beneficial to label ...
Tijana Zrnic, Emmanuel J. Candès
openaire   +3 more sources

Sustainability under Active Inference

Systems
In this paper, we explore the known connection among sustainability, resilience, and well-being within the framework of active inference. Initially, we revisit how the notions of well-being and resilience intersect within active inference before defining
Mahault Albarracin, Maxwell Ramstead, Riddhi J. Pitliya, Ines Hipolito, Lancelot Da Costa, Maria Raffa, Axel Constant, Sarah Grace Manski   +7 more
doaj   +1 more source

Learning action-oriented models through active inference.

PLoS Computational Biology, 2020
Converging theories suggest that organisms learn and exploit probabilistic models of their environment. However, it remains unclear how such models can be learned in practice.
Alexander Tschantz, Anil K Seth, Christopher L Buckley   +2 more
doaj   +1 more source

An Active Inference Model of Collective Intelligence

Entropy, 2021
Collective intelligence, an emergent phenomenon in which a composite system of multiple interacting agents performs at levels greater than the sum of its parts, has long compelled research efforts in social and behavioral sciences.
Rafael Kaufmann, Pranav Gupta, Jacob Taylor   +2 more
doaj   +1 more source

Comparative Evaluation of Hemodiafiltration, Hemoperfusion, and Standard Hemodialysis on Efficacy, Inflammatory Control, Dialysis Adequacy, and Safety in End‐Stage Renal Disease: A Prospective Observational Study

Therapeutic Apheresis and Dialysis, EarlyView.
ABSTRACT Background Chronic micro‐inflammation in patients with end‐stage renal disease (ESRD) is a significant driver of cardiovascular complications and diminished quality of life. While standard hemodialysis (SHD) effectively manages small‐molecule clearance, its ability to remove medium‐to‐large uremic toxins—the primary catalysts of systemic ...
Hongwei Zuo, Weisi Dai, Jie Mao, Mei Ye, Xingshan Lu, Xiaocui Zhang   +5 more
wiley   +1 more source

Dopamine, reward learning, and active inference

Frontiers in Computational Neuroscience, 2015
Temporal difference learning models propose phasic dopamine signalling encodes reward prediction errors that drive learning. This is supported by studies where optogenetic stimulation of dopamine neurons can stand in lieu of actual reward.
Thomas eFitzgerald, Ray eDolan, Ray eDolan, Karl eFriston   +3 more
doaj   +1 more source