Advances in Logical and Quantitative Methods for Complex Systems

The field of complex systems is witnessing a significant shift towards the development of more sophisticated logical and quantitative methods. Researchers are increasingly focusing on the application of monadic second order logic and bisimulation pseudometrics to analyze and understand complex systems. This direction is driven by the need to capture the intricate patterns and behaviors of these systems, and to develop more effective tools for their analysis and optimization. Noteworthy papers in this area include: The paper on Functional Matching of Logic Subgraphs, which introduces a novel approach to identifying function-related subgraphs in logic circuits, and achieves significant performance improvements over existing structural methods. The paper on Expressivity of bisimulation pseudometrics over analytic state spaces, which develops a quantitative modal logic for Markov decision processes and proves a quantitative form of Hennessy-Milner theorem.

Sources

Multidimensional tilings and MSO logic

Functional Matching of Logic Subgraphs: Beyond Structural Isomorphism

Expressivity of bisimulation pseudometrics over analytic state spaces

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