In deterministic partially observable worlds, perfect prediction requires either identifying the relevant hidden quotient or achieving overwrite control, while high empowerment alone is insufficient.
Journal of Mathematical Psychology 99, 102447 (2020)
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Active inference offers a variational way to phenotype agency in AI systems by measuring empowerment in generative models via a T-maze paradigm.
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Prediction and Empowerment: A Theory of Agency through Bridge Interfaces
In deterministic partially observable worlds, perfect prediction requires either identifying the relevant hidden quotient or achieving overwrite control, while high empowerment alone is insufficient.
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Active Inference: A method for Phenotyping Agency in AI systems?
Active inference offers a variational way to phenotype agency in AI systems by measuring empowerment in generative models via a T-maze paradigm.