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The Free Energy Principle for Perception and Action: A Deep Learning Perspective
Entropy, 2022 The free energy principle, and its corollary active inference, constitute a bio-inspired theory that assumes biological agents act to remain in a restricted set of preferred states of the world, i.e., they minimize their free energy. Under this principle,
Pietro Mazzaglia +3 more
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Successor Representation Active Inference
CoRR, 2022 Recent work has uncovered close links between between classical reinforcement learning algorithms, Bayesian filtering, and Active Inference which lets us understand value functions in terms of Bayesian posteriors. An alternative, but less explored, model-free RL algorithm is the successor representation, which expresses the value function in terms of a
Beren Millidge, Christopher L. Buckley
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Frontiers in SociologyGeneral 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
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Uncertainty, epistemics and active inference [PDF]
Journal of The Royal Society Interface, 2017 Abstract Biological systems—like ourselves—are constantly faced with uncertainty. Despite noisy sensory data, and volatile environments, creatures appear to actively maintain their integrity. To account for this remarkable ability to make optimal decisions in the face of a capricious world, we propose a generative model that ...
Thomas Parr, Karl J. Friston
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Modelling of a Flexible Manoeuvring System Using ANFIS Techniques [PDF]
, 2010 The increased utilization of flexible structure systems, such as flexible manipulators and flexible aircraft in various applications, has been motivated by the requirements of industrial automation in recent years.
Bin Zaidan, Martha Arbayani +2 more
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EntropyThe 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 +3 more
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Action understanding and active inference [PDF]
Biological Cybernetics, 2011 We have suggested that the mirror-neuron system might be usefully understood as implementing Bayes-optimal perception of actions emitted by oneself or others. To substantiate this claim, we present neuronal simulations that show the same representations can prescribe motor behavior and encode motor intentions during action-observation.
Karl J. Friston +2 more
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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 +2 more
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CoRRInspired 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
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Sustainability under Active Inference
SystemsIn 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 +7 more
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