15 citations · 23 across the 8 of their papers we have counts for
9 papers
Normative active inference: A numerical proof of principle for a computational and economic legal analytic approach to AI governance
Axel Constant, Mahault Albarracin, Karl J. Friston
This paper presents a computational account of how legal norms can influence the behavior of artificial intelligence (AI) agents, grounded in the active inference framework (AIF) t…
Dynamic Causal Models of Time-Varying Connectivity
Johan Medrano, Karl J. Friston, Peter Zeidman
This paper introduces a novel approach for modelling time-varying connectivity in neuroimaging data, focusing on the slow fluctuations in synaptic efficacy that mediate neuronal dy…
A framework for the use of generative modelling in non-equilibrium statistical mechanics
Karl J Friston, Maxwell J D Ramstead, Dalton A R Sakthivadivel
We discuss an approach to mathematically modelling systems made of objects that are coupled together, using generative models of the dependence relationships between states (or tra…
Bayesian sparsification for deep neural networks with Bayesian model reduction
Dimitrije Marković, Karl J. Friston, Stefan J. Kiebel
Deep learning's immense capabilities are often constrained by the complexity of its models, leading to an increasing demand for effective sparsification techniques. Bayesian sparsi…
Life-inspired Interoceptive Artificial Intelligence for Autonomous and Adaptive Agents
Sungwoo Lee, Younghyun Oh, Hyunhoe An +4
Building autonomous -- i.e., choosing goals based on one's needs -- and adaptive -- i.e., surviving in ever-changing environments -- agents has been a holy grail of artificial inte…
Canonical Cortical Field Theories
Gerald K. Cooray, Vernon Cooray, Karl Friston
We characterise the dynamics of neuronal activity, in terms of field theory, using neural units placed on a 2D-lattice modelling the cortical surface. The electrical activity of ne…
Linking fast and slow: the case for generative models
Johan Medrano, Karl J. Friston, Peter Zeidman
A pervasive challenge in neuroscience is testing whether neuronal connectivity changes over time due to specific causes, such as stimuli, events, or clinical interventions. Recent…
Natural Language Syntax Complies with the Free-Energy Principle
Elliot Murphy, Emma Holmes, Karl Friston
Natural language syntax yields an unbounded array of hierarchically structured expressions. We claim that these are used in the service of active inference in accord with the free-…
Global dynamics of neural mass models
Gerald Cooray, Richard Rosch, Karl Friston
Neural mass models are used to simulate cortical dynamics and to explain the electrical and magnetic fields measured using electro- and magnetoencephalography. Simulations evince a…