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Related papers: Function, Complexity and Thermodynamics in Adaptiv…

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Predicting future observations plays a central role in machine learning, biology, economics, and many other fields. It lies at the heart of organizational principles such as the variational free energy principle and has even been shown --…

Machine Learning · Computer Science 2025-04-09 Lukas J. Fiderer , Paul C. Barth , Isaac D. Smith , Hans J. Briegel

In the theoretical modelling of a physical system a crucial step consists in the identification of those degrees of freedom that enable a synthetic, yet informative representation of it. While in some cases this selection can be carried out…

Statistical Mechanics · Physics 2020-06-30 Marco Giulini , Roberto Menichetti , M. Scott Shell , Raffaello Potestio

Recent advances in physics-augmented neural networks have enabled thermodynamically consistent data-driven constitutive modeling of complex inelastic materials. Most existing approaches, however, implicitly adopt a specific thermodynamic…

Materials Science · Physics 2026-05-28 Reese E. Jones , Jan N. Fuhg

Key to biological success, the requisite variety that confronts an adaptive organism is the set of detectable, accessible, and controllable states in its environment. We analyze its role in the thermodynamic functioning of information…

Statistical Mechanics · Physics 2017-04-26 Alexander B. Boyd , Dibyendu Mandal , James P. Crutchfield

Complexity science offers a wide range of measures for quantifying unpredictability, structure, and information. Yet, a systematic conceptual organization of these measures is still missing. We present a unified framework that locates…

Machine Learning · Computer Science 2025-05-13 Nima Dehghani

This paper proposes a simple model to capture the complexity of multi-layer systems where their constituent layers affect, are affected by, each other. The physical layer is a circuit composed by a power source and resistors in parallel.…

Multiagent Systems · Computer Science 2016-02-09 Florian Kühnlenz , Pedro H. J. Nardelli

To help evaluate and understand the latent capabilities of language models, this paper introduces an approach using optimized input embeddings, or 'soft prompts,' as a metric of conditional distance between a model and a target behavior.…

Machine Learning · Computer Science 2025-05-22 Ross Nordby

Soft materials, such as colloidal suspensions, polymer solutions, and biological systems, are typically multicomponent mixtures of macromolecules and simpler components (e.g., microions, monomers, solvent) that can assemble into complex…

Soft Condensed Matter · Physics 2015-05-13 Alan R. Denton

We introduce materiomusic as a generative framework linking the hierarchical structures of matter with the compositional logic of music. Across proteins, spider webs and flame dynamics, vibrational and architectural principles recur as…

Machine Learning · Computer Science 2026-01-06 Markus J. Buehler

Performance-influence models are beneficial for understanding how configurations affect system performance, but their creation is challenging due to the exponential growth of configuration spaces. While gray-box approaches leverage…

Software Engineering · Computer Science 2025-09-22 Omid Gheibi , Christian Kästner , Pooyan Jamshidi

Information-processing systems that coordinate multiple agents and objectives face fundamental thermodynamic constraints. We show that solutions with maximum utility to act as coordination focal points have a much higher selection pressure…

Artificial Intelligence · Computer Science 2025-10-16 Atma Anand

In the 21st century, many of the crucial scientific and technical issues facing humanity can be understood as problems associated with understanding, modelling, and ultimately controlling complex systems: systems comprised of a large number…

Information Theory · Computer Science 2025-01-20 Thomas F. Varley

We develop an axiomatic reconstruction of thermodynamics based entirely on two primitive components: a description of what aspects of a system are observed and a reference measure that encodes the underlying descriptive convention. These…

Chemical Physics · Physics 2026-01-21 Tatsuaki Tsuruyama

The Free Energy Principle (FEP) is a leading framework for mathematically modeling self-organization and learning, while Integrated Information Theory (IIT) is a computational ontology of consciousness oriented around irreducible cause and…

Neurons and Cognition · Quantitative Biology 2026-05-14 Alexander Kearney

Humans rely on multimodal perception to form representations of the world. This implies that environmental stimuli must remain consistent and predictable throughout their journey to our sensory organs. When it comes to vision,…

Materials Science · Physics 2024-08-14 Thomas Daunizeau , Sinan Haliyo , Vincent Hayward

One fascinating aspect of the brain is its ability to process information in a fast and reliable manner. The functional architecture is thought to play a central role in this task, by encoding efficiently complex stimuli and facilitating…

Neurons and Cognition · Quantitative Biology 2016-02-17 Alberto Romagnoni , Jérôme Ribot , Daniel Bennequin , Jonathan D. Touboul

Fisher information, Shannon information entropy and Statistical Complexity are calculated for the interface of a normal metal and a superconductor, as a function of the temperature for several materials. The order parameter $\Psi({\bf r})$…

Quantum Physics · Physics 2018-06-05 Ch. C. Moustakidis , C. P. Panos

Integrated information theory (IIT) argues that the substrate of consciousness is a maximally irreducible complex of units. Together, subsets of the complex specify a cause-effect structure, composed of distinctions and their relations,…

Neurons and Cognition · Quantitative Biology 2025-01-03 William G. P. Mayner , Bjørn Erik Juel , Giulio Tononi

Biological systems process information under noisy environment. Sensory adaptation model of E. coli is suitable for investigation because of its simplicity. To understand the adaptation processing quantitatively, stochastic thermodynamic…

Molecular Networks · Quantitative Biology 2019-07-16 Keita Ashida , Kotaro Oka

Natural organisms can convert environmental stimuli into sensory feedback to regulate their body and realize active adaptivity. However, realizing such a feedback-regulation mechanism in synthetic material systems remains a grand challenge.…

Robotics · Computer Science 2024-12-23 Jianfeng Yang , Haotian Pi , Zixuan Deng , Hongshuang Guo , Wan Shou , Hang Zhang , Hao Zeng