Results 31 to 40 of about 5,838,744 (309)
Hunter–gatherer foraging networks promote information transmission
Royal Society Open Science, 2021 Central-place foraging (CPF), where foragers return to a central location (or home), is a key feature of hunter–gatherer social organization. CPF could have significantly changed hunter–gatherers’ spatial use and mobility, altered social networks and ...
Ketika Garg +3 more
doaj +1 more source
Active inference through whiskers [PDF]
Neural Networks, 2021 AbstractRodents use whisking to probe actively their environment and to locate objects in space, hence providing a paradigmatic biological example of active sensing. Numerous studies show that the control of whisking has anticipatory aspects. For example, rodents target their whisker protraction to the distance at which they expect objects, rather than
Mannella, Francesco +3 more
openaire +2 more sources
Designing explainable artificial intelligence with active inference: A framework for transparent introspection and decision-making [PDF]
International Workshop on Affective Interactions, 2023 This paper investigates the prospect of developing human-interpretable, explainable artificial intelligence (AI) systems based on active inference and the free energy principle. We first provide a brief overview of active inference, and in particular, of
Mahault Albarracin +6 more
semanticscholar +1 more source
, 2021 Active inference is a unifying theory for perception and action resting upon the idea that the brain maintains an internal model of the world by minimizing free energy. From a behavioral perspective, active inference agents can be seen as self-evidencing beings that act to fulfill their optimistic predictions, namely preferred outcomes or goals.
Mazzaglia, Pietro +2 more
openaire +3 more sources
Learning perception and planning with deep active inference [PDF]
, 2020 Active inference is a process theory of the brain that states that all living organisms infer actions in order to minimize their (expected) free energy. However, current experiments are limited to predefined, often discrete, state spaces.
Catal, Ozan +4 more
core +2 more sources
Control Flow in Active Inference Systems—Part I: Classical and Quantum Formulations of Active Inference [PDF]
IEEE Transactions on Molecular Biological and Multi-Scale Communications, 2023 Living systems face both environmental complexity and limited access to free-energy resources. Survival under these conditions requires a control system that can activate, or deploy, available perception and action resources in a context specific way. In
C. Fields +6 more
semanticscholar +1 more source
A step-by-step tutorial on active inference and its application to empirical data
Journal of Mathematical Psychology, 2021 The active inference framework, and in particular its recent formulation as a partially observable Markov decision process (POMDP), has gained increasing popularity in recent years as a useful approach for modeling neurocognitive processes.
Ryan Smith +2 more
semanticscholar +1 more source
On efficient computation in active inference [PDF]
Expert systems with applications, 2023 Despite being recognized as neurobiologically plausible, active inference faces difficulties when employed to simulate intelligent behaviour in complex environments due to its computational cost and the difficulty of specifying an appropriate target ...
Aswin Paul +3 more
semanticscholar +1 more source
Cognitive effort and active inference
Neuropsychologia, 2023 This paper aims to integrate some key constructs in the cognitive neuroscience of cognitive control and executive function by formalising the notion of cognitive (or mental) effort in terms of active inference.
Thomas Parr +3 more
semanticscholar +1 more source
Modeling Motor Control in Continuous Time Active Inference: A Survey [PDF]
IEEE Transactions on Cognitive and Developmental Systems, 2023 The way the brain selects and controls actions is still widely debated. Mainstream approaches based on optimal control focus on stimulus-response mappings that optimize cost functions.
Matteo Priorelli +7 more
semanticscholar +1 more source