Author

Michael Levin

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Conference Open access Aug 2026

The Informationally Integrated Alignment Hypothesis: Integrated Information Aligns with and Predicts Final Reward in Reinforcement Learning Agents

A hallmark of life on Earth is the ability of agents to exert causal power and be drivers of subsequent events. This is key to cognition at all scales. Integrated information, measuring the degree to which an agent exerts unique predictive power on its future, is one consequence of causal power. Indeed, recent discover...

F. Pigozzi, Michael Levin · IEEE Symposium on Artificial... · 0 citations

#machine learning Preprint Sep 2026

On Growth and Form, and Function: Reusable Regulatory Handles Control Phenotypic Variation

How phenotypic transformations are implemented by changes in underlying regulatory dynamics remains a central question in developmental biology. Inspired by D'Arcy Thompson's 1917"On Growth and Form", we ask whether coherent large-scale transformations of morphology can be encoded as low-dimensional modulations of a se...

Benedikt Hartl, Milton L. Montero, Marcello Barylli et al. · 0 citations

#artificial intelligence Conference Open access Jun 2026

The Artificial Experimentalist: Discovery and Control of Self-Organizing Phenomena with Autotelic Reinforcement Learning

A closed-loop framework based on autotelic reinforcement learning is introduced, in which an agent autonomously samples diverse goals and learns a goal-conditioned policy to intervene in a complex system through minimal, local perturbations, suggesting a path toward artificial experimentalist agents that, autonomously...

Marko Cvjetko, Benedikt Hartl, Michael Levin et al. · IEEE Symposium on Artificial... · 0 citations