Results 11 to 20 of about 3,696,970 (268)
Scaling Active Inference [PDF]
2020 International Joint Conference on Neural Networks (IJCNN), 2020 In reinforcement learning (RL), agents often operate in partially observed and uncertain environments. Model-based RL suggests that this is best achieved by learning and exploiting a probabilistic model of the world.
Anil. K. Seth +7 more
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Resilience and Active Inference
Frontiers in Psychology, 2022 In this paper, we aim to conceptualize and formalize the construct of resilience using the tools of active inference, a new physics-based modeling approach apt for the description and analysis of complex adaptive systems. We intend this as a first step towards a computational model of resilient systems.
Mark Miller +14 more
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Contextual perception under active inference [PDF]
Scientific Reports, 2021 Human social interactions depend on the ability to resolve uncertainty about the mental states of others. The context in which social interactions take place is crucial for mental state attribution as sensory inputs may be perceived differently depending
Parr, T. +4 more
core +2 more sources
Contrastive Active Inference [PDF]
CoRR, 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
Verbelen, Tim +2 more
core +6 more sources
Reinforcement learning or active inference? [PDF]
PLoS ONE, 2009 This paper questions the need for reinforcement learning or control theory when optimising behaviour. We show that it is fairly simple to teach an agent complicated and adaptive behaviours using a free-energy formulation of perception.
Friston, K. +17 more
core +3 more sources
, 2022 The first comprehensive treatment of active inference, an integrative perspective on brain, cognition, and behavior used across multiple disciplines.
Parr, Thomas +2 more
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Active Inferants: An Active Inference Framework for Ant Colony Behavior [PDF]
Frontiers in Behavioral Neuroscience, 2021 In this paper, we introduce an active inference model of ant colony foraging behavior, and implement the model in a series of in silico experiments. Active inference is a multiscale approach to behavioral modeling that is being applied across settings in theoretical biology and ethology.
Daniel Ari Friedman +9 more
openaire +7 more sources
Active Inference: Demystified and Compared [PDF]
Neural Computation, 2021 Active inference is a first principle account of how autonomous agents operate in dynamic, nonstationary environments. This problem is also considered in reinforcement learning, but limited work exists on comparing the two approaches on the same discrete-
Friston, KJ, Sajid, N, Ball, PJ, Parr, T
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Active Inference and Auditory Hallucinations [PDF]
Computational Psychiatry, 2018 Auditory verbal hallucinations (AVH) are often distressing symptoms of several neuropsychiatric conditions, including schizophrenia. Using a Markov decision process formulation of active inference, we develop a novel model of AVH as false (positive) inference.
Benrimoh, D +4 more
doaj +7 more sources
Dopamine, Affordance and Active Inference
PLoS Computational Biology, 2012 The role of dopamine in behaviour and decision-making is often cast in terms of reinforcement learning and optimal decision theory. Here, we present an alternative view that frames the physiology of dopamine in terms of Bayes-optimal behaviour. In this account, dopamine controls the precision or salience of (external or internal) cues that engender ...
Karl J. Friston +9 more
openaire +10 more sources