Results 61 to 70 of about 3,880,038 (272)

Transcendental model selection: a computational account of symbolic cognition and general intelligence through morality and culture

Frontiers in Sociology
General intelligence enables flexible problem solving across diverse contexts by minimizing uncertainty. Symbolic systems such as language extend this capacity, allowing humans to build social groups and construct world models beyond typical biological ...
Shagor Rahman, Andrew Pashea
doaj   +1 more source

The Embodied Hijack: when Pleistocene minds meet disembodied artificial intelligence

Frontiers in Psychology
The rapid integration of artificial intelligence into everyday life has intensified a long-standing feature of human cognition: the attribution of agency, intention, and understanding to nonhuman systems.
Sheila L. Macrine, Sheila L. Macrine
doaj   +1 more source

Active inference and the two-step task

Scientific Reports, 2022
Sequential decision problems distill important challenges frequently faced by humans. Through repeated interactions with an uncertain world, unknown statistics need to be learned while balancing exploration and exploitation.
Sam Gijsen, Miro Grundei, Felix Blankenburg   +2 more
doaj   +1 more source

Reward Maximization Through Discrete Active Inference [PDF]

, 2023
Active inference is a probabilistic framework for modeling the behavior of biological and artificial agents, which derives from the principle of minimizing free energy.
Parr, Thomas, Da Costa, Lancelot, Smith, Ryan, Sajid, Noor, Friston, Karl   +4 more
core   +1 more source

Modeling Sustainable Resource Management using Active Inference [PDF]

Active inference helps us simulate adaptive behavior and decision-making in biological and artificial agents. Building on our previous work exploring the relationship between active inference, well-being, resilience, and sustainability, we present a ...
Raffa, Maria, Kinghorn, Paul, Albarracin, Mahault, Hipolito, Ines, Stoianov I. P., Cialfi D., Shimazaki H., Lanillos P., Pitliya R. J., Verbelen T., Wisse M., Sajid N., Buckley C. L.   +12 more
core   +1 more source

Hierarchical Gaussian Filtering of Sufficient Statistic Time Series for Active Inference

, 2020
Active inference relies on state-space models to describe the environments that agents sample with their actions. These actions lead to state changes intended to minimize future surprise.
Lilian Weber, Christoph Mathys, Mathys C., Weber L.   +3 more
core   +1 more source

Aligning Active Inference Ontology to SUMO

<p><span>This document aims to act as a scaffolding, displaying a tentative alignment of Active Inference terms with SUMO entities, in order to facilitate the anticipated process of rigorously mapping Active Inference to the SUMO formal ...
Sayeg, Paulo Duare Andrade, Iennaco, Maria Luiza, Tickles, Dean, Vyatkin, Alex, Douglass, David S., Rahmjoo, Ali, Chokhalingam, Rhea, Pease, Adam, Smékal, Jakub, Maybell, Scott Ryan, Friedman, Daniel Ari, Knight, V. Bleu, Balbuena, Jessica Angeli, Hurtado, Ana Magdalena   +13 more
core   +2 more sources

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

Active inference for Robot control: A Factor Graph Approach [PDF]

, 2019
Active Inference provides a framework for perception,action and learning, where the optimization is done byminimizing the Free-Energy of a system. This paperexplores whether active inference can be used for closedloopcontrol of a 1 degree of freedom ...
Vanderbroeck, Mees, van der Werf, Tiis, Baioumy, Mohamed, van der Lans, Daan, de Rooij, Rens   +4 more
core   +1 more source

Transcript of: Karl Friston, 1st Applied Active Inference Symposium, Active Inference Lab, June 21, 2021

, 2021
On June 21st, 2021, Active Inference Lab (activeinference.org/) hosted its first Applied Active Inference Symposium, featuring Professor Karl Friston. The Symposium was structured in three sections, corresponding to the Organizational Units of the Active
Sganzerla, Lorena, Sillett, Stephen, Metelkin, Ivan, Tickles, Dean, Vyatkin, Alex, Friston, Karl, Friedman, Daniel Ari, Douglass, David Standish, Iennaco de Vasconcelos, Maria Luiza   +8 more
core   +1 more source