Evolution of Physical Intelligence Across Scales
By following the evolution of physical intelligence across scales, this article shows how intelligence arises from materials, structures, physical interactions, and collectives. It establishes physical intelligence as the evolutionary foundation upon which embodied intelligence is built.
Ke Liu +7 more
wiley +1 more source
Interplay Between Vertical and Horizontal Schemes of Computation: From Bayesian Inference to Quantum Logic via Gluing Boolean Algebras. [PDF]
Gunji YP +7 more
europepmc +1 more source
A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws
The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows +7 more
wiley +1 more source
Dwell-photo nodes in classical garden tourism: a multimodal spatial analysis of Yipu. [PDF]
Zhang F, Wu Z, Zhou X.
europepmc +1 more source
A Semantic Tableau Version of First-Order Quasi-Classical Logic
Quasi-classical logic (QC logic) allows the derivation of nontrivial classical inferences from inconsistent information. A paraconsistent, or non-trivializable, logic is, by necessity, a compromise, or weakening, of classical logic. The compromises on
Anthony Hunter
core
LLM‐Based Scientific Assistants for Knowledge Extraction: Which Design Choices Matter?
A comprehensive framework for optimizing Large Language Models in domain‐specific applications is introduced. The LLM Playground integrates Prompt Engineering, knowledge augmentation, and advanced reasoning strategies to enable systematic comparison of architectures and base models.
David Exler +7 more
wiley +1 more source
Robust and intelligent control strategies for a 3-DOF robotic arm: a comparative study. [PDF]
Esmail EE, El-Khatib MF, Agwa MA.
europepmc +1 more source
Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley +1 more source
Adaptive fuzzy sliding mode control applied to inverted pendulum. [PDF]
Mohammed TK +3 more
europepmc +1 more source

